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数据挖掘教程

2008-11-20 06:32:41

本书翻译自"Data Mining A Tutorial-Based Primer"，是一本很好的数据挖掘的入门教程。本书介绍了数据挖掘的基本过程，包括完整的数据挖掘流程的介绍、大多数流行数据挖掘技术的展示以及一个基于EXcel的数据挖掘工具iDA的详细展示，其实它的英文名能突出它的入门性质。本书解释了如何将数据挖掘应用于解决实际问题，从而使你能将数据挖掘技术应用于自己的实际工作中去本书讲述了数据挖掘和知识发现的各方面内容，并着重介绍了数据挖掘模型的建立与测试，以及数据挖掘结果的解释与验证等内容。

Advanced Data Mining Techniques

2008-11-08 06:36:14

目录如下：
Part I: Introduction
Chapter 1 gives an overview of data mining, and provides a description of
the data mining process. An overview of useful business applications is
provided.
Chapter 2 presents the data mining process in more detail. It demonstrates
this process with a typical set of data. Visualization of data through data
mining software is addressed.
Part II: Data Mining Methods as Tools
Chapter 3 presents memory-based reasoning methods of data mining.
Major real applications are described. Algorithms are demonstrated with
prototypical data based on real applications.
Chapter 4 discusses association rule methods. Application in the form of
market basket analysis is discussed. A real data set is described, and a simplified
version used to demonstrate association rule methods.
Chapter 5 presents fuzzy data mining approaches. Fuzzy decision tree approaches
are described, as well as fuzzy association rule applications. Real
data mining applications are described and demonstrated
Chapter 6 presents Rough Sets, a recently popularized data mining method.
Chapter 7 describes support vector machines and the types of data sets in
which they seem to have relative advantage.
Chapter 8 discusses the use of genetic algorithms to supplement various
data mining operations.
Chapter 9 describes methods to evaluate models in the process of data
mining.
Part III: Applications
Chapter 10 presents a spectrum of successful applications of the data mining
techniques, focusing on the value of these analyses to business decision
making.

Time Series Knowledge Mining

2008-11-05 08:06:40

德国著名大学－马堡大学(Philipps-University Marburg)2006年的一篇博士论文,关于时序数据挖掘方面的。Abstract:
An important goal of knowledge discovery is the search for patterns in data that can help explain
the underlying process that generated the data. The patterns are required to be new,
useful, and understandable to humans. In this work we present a new method for the understandable
description of local temporal relationships in multivariate data, called Time Series
Knowledge Mining (TSKM). We dene the Time Series Knowledge Representation (TSKR) as
a new language for expressing temporal knowledge. The patterns have a hierarchical structure,
each level corresponds to a single temporal concept. On the lowest level, intervals are used
to represent duration. Overlapping parts of intervals represent coincidence on the next level.
Several such blocks of intervals are connected with a partial order relation on the highest level.
Each pattern element consists of a semiotic triple to connect syntactic and semantic information
with pragmatics. The patterns are very compact, but oer details for each element on demand.
In comparison with related approaches, the TSKR is shown to have advantages in robustness,
expressivity, and comprehensibility. Ecient algorithms for the discovery of the patterns are
proposed. The search for coincidence as well as partial order can be formulated as variants of
the well known frequent itemset problem. One of the best known algorithms for this problem
is therefore adapted for our purposes. Human interaction is used during the mining to analyze
and validate partial results as early as possible and guide further processing steps. The ecacy
of the methods is demonstrated using several data sets. In an application to sports medicine
the results were recognized as valid and useful by an expert of the eld.

快易通AutoCAD 数据库应用与连接技术

2008-09-23 10:39:55

这是一本介绍 AutoCAD 2000的数据库连接技术的书，重点讲述了如何将数据库连接技术应用于实际工作中，以及如何利用数据库连接技术对AuotCAD 2000进行二次开发。
AutoCAD作为 PC平台上的最流行的CAD系统，正被越来越广泛地使用。AutoCAD 2000提供的数据库连接技术及其二次开发环境，在易用性、兼容性等方面比老版本的AutoCAD的外部数据库接口技术有了很大的提高。本书从初次使用AutoCAD数据库连接技术的一般用户的角度出发，介绍了在实际工作中利用数据库连接技术提高工作效率的方法；对于有基本编程能力的AutoCAD用户和AutoCAD二次开发人员，介绍了利用数据库连接技术对 AutoCAD进行二次开发的方法，同时提供了在 VBA、VB 6.0、ObjectARX 2000 SDK及DelPhi 4.0上开发数据库连接技术的方法和实例。
全书内容丰富新颖，由浅入深，易学易用，适用于熟悉AutoCAD的使用方法并具备基本的编程知识的AutoCAD用户和 AutoCAD 2000的二次开发人员。

Inside XML

2008-09-18 07:35:04

Inside XML is an intelligent and easy-to-follow guide to today's proliferating XML standards. Aside from being a road map to the latest and greatest in what's on the horizon with XML, this book gives you what you need to know to be productive with existing XML tools right now.
The tour begins with an introduction to the XML used in real-world applications (like the Chemical Markup Language, CML, and the Vector Markup Language, VML [for graphics]). While many books give you the basics, this one excels at explaining the conventions of designing robust XML document types in detail. With dozens of short examples, you'll learn XML conventions thoroughly, including some of the best practices for creating readable, maintainable content. The author highlights certain lines of XML code, so it's easier to see what's important.

After 200 pages of in-depth material on how to design XML documents, the book turns to using XML in actual browsers (both in Netscape and Internet Explorer). This practical focus means that you get to explore available Microsoft tools and how they sometimes differ from official W3C standards.

Subsequent sections turn to related XML standards, like XLinks and XPointers. Each section lists Web links to the latest online documents, but the emphasis isn't on theory so much as on what you can do right now. You'll learn how to use Java with XML, including navigating the XML Document Object Model (DOM) using IBM's XML for Java (XML4J) package. The tutorial explaining the Simple API for XML (SAX) does a great job of explaining the advantages of this popular tool.

Final chapters delve into displaying XML with several existing standards, including XHTML (for Web browser content), VML (for drawing shapes), and the Resource Description Framework (RDF) for allowing XML-based content searching. Final sections look at combining XML with Perl and Java (through servlets and JSPs) and give a glimpse at wireless content created with the Wireless Markup Language (WML).

Suitable for any developer or IT manager who needs to understand and use XML, Inside XML provides an authoritative yet approachable source of information on a fast-changing set of standards that are almost sure to revolutionize computing over the next few years. --Richard Dragan

Topics covered:

Comprehensive introduction to XML basics and tools
Designing XML documents (including "well-formed" XML, tags and elements, and attributes and namespaces)
Document Type Definitions (DTDs)
Entities and attributes (including design documents)
XML Schemas (using Internet Explorer)
Introduction to JavaScript
Using JavaScript with the XML Document Object Model (DOM)
Cascading style sheets (CSS)
Overview of basic Java programming
Parsing XML with IBM's XML for Java (XML4J)
Java and the Simple API for XML (SAX)
XSL transformations (XSL style sheets and XSL formatting objects)
XLinks and XPointers
Introduction to XHTML
The Resource Description Framework (RDF)
The Microsoft Channel Definition Format (CDF)
The Vector Markup Language (VML)
Using XML with Java
Perl and ASP on the server
Quick introduciton to the Wireless Markup Language (WML)
Reference to the XML 1.0 Specification

Product Description

The XML explosion hardly needs any introduction-it's everywhere and there just seems to be no end to what can be done with XML. While writing to the W3C standards, and keeping up with the pace for corporate implementation, you, the programmer or web developer, will need a comprehensive guide to get you started and show you what XML and its related technologies can do. A thorough guide is imperative to success because you will need to know and understand the full scope of XML from day one in order to work with it successfully. With your time constraints and impossible project schedules, you need a comprehensive guide that fulfills your needs in one complete book. Inside XML is an anchor book that covers both the Microsoft and non-Microsoft approach to XML programming. It covers in detail the hot aspects of XML; such as, DTD's vs. XML Schemas, CSS, XSL, XSLT, Xlinks, Xpointers, XHTML, RDF, CDF, parsing XML in Perl and Java, and much more.

SAS GRAPHIC FOR JAVA

2008-08-11 22:38:52

2007. SAS? Graphics for Java: Examples Using SAS? AppDev Studio? and the Output Delivery System. Cary,
NC: SAS Institute Inc.
SAS? Graphics for Java: Examples Using SAS? AppDev Studio? and the Output Delivery System
Copyright ? 2007, SAS Institute Inc., Cary, NC, USA
ISBN 978-1-59047-693-2
All rights reserved. Produced in the United States of America.
For a hard-copy book: No part of this publication may be reproduced, stored in a retrieval system, or
transmitted, in any form or by any means, electronic, mechanical, photocopying, or otherwise, without the
prior written permission of the publisher, SAS Institute Inc.
For a Web download or e-book: Your use of this publication shall be governed by the terms established by
the vendor at the time you acquire this publication.
U.S. Government Restricted Rights Notice: Use, duplication, or disclosure of this software and related
documentation by the U.S. government is subject to the Agreement with SAS Institute and the restrictions set
forth in FAR 52.227-19, Commercial Computer Software-Restricted Rights (June 1987).
SAS Institute Inc., SAS Campus Drive, Cary, North Carolina 27513.
1st printing, May 2007
SAS? Publishing provides a complete selection of books and electronic products to help customers use SAS
software to its fullest potential. For more information about our e-books, e-learning products, CDs, and hardcopy
books, visit the SAS Publishing Web site at support.sas.com/pubs or call 1-800-727-3228.
SAS? and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS
Institute Inc. in the USA and other countries. ? indicates USA registration.
Other brand and product names are registered trademarks or trademarks of their respective companies.

Acknowledgments ix
Introduction xi
Part 1 SAS AppDevStudio 1
Chapter 1 Getting Started with SAS AppDev Studio 3
1.1 Tag Libraries for SAS AppDev Studio 3
1.2 Getting Ready to Add Graphs to Your SAS AppDev Studio
Project 8
1.3 Your Data 10
1.3.1 Tips and Information 11
Chapter 2 SAS AppDev Studio Custom Tags and Attributes for
Basic Graphs 13
2.1 SAS AppDev Studio 2 Tags 15
2.1.1 sasads:Bar 15
2.1.2 sasads:Combination 16
2.1.3 sasads:Pie 16
2.1.4 sasads:Scatter 17
2.1.5 sasads:SegmentedBar 17
2.2 SAS AppDev Studio 3 Tags 18
2.2.1 sas:BarChart 18
2.2.2 sas:BarLineChart 19
2.2.3 sas:LineChart 20
2.2.4 sas:LinePlot 21
2.2.5 sas:PieChart 22
2.2.6 sas:RadarChart 23
2.2.7 sas:ScatterPlot 24
2.3 Common Attributes 25

Chapter 3 SAS AppDev Studio 3 Graph Model Tags 39
3.1 BarChartModel 40
3.2 BarLineChartModel 50
3.3 LineChartModel 64
3.4 LinePlotModel 67
3.5 PieChartModel 74
3.6 RadarChartModel 87
3.7 ScatterPlotModel 92
3.7.1 Baselines 97
Chapter 4 Nested Tags for Graph Models 99
4.1 Axis Models 100
4.1.1 Response Axis Baseline Models 107
4.1.2 Corresponding Graph Models 108
4.1.3 Column and Row Axis Models 110
4.2 Legends 111
4.2.1 Corresponding Graph Models 113
4.3 Line Style Tags 113
4.3.1 Corresponding Graph Models 116
4.4 Text Style Tags 116
4.4.1 Corresponding Graph Models 117
4.5 AxisWallModel 118
4.6 BackgroundFillStyle 119
4.6.1 Corresponding Graph Models 122
4.7 DataElementStyle 123
4.8 DataTipModel 123
4.9 SubgroupLabelModel 124
Chapter 5 Supporting Tags 125
5.1 Fill Tags 126
5.2 Line Tags 130
5.2.1 AxisLineStyle, GridLineStyle, StrokeLineStyle,
FrameLineStyle, and OutlineLineStyle
5.2.2 BasicStroke 133

5.3 Text Tags 133
5.3.1 Font 133
5.3.2 LabelTextStyle and ValueTextStyle 134
5.3.3 TextStyle 136
5.3.4 ShadowStyle 136
5.4 Tick Mark Tags 136
5.5 Miscellaneous Tags 137
5.5.1 DiscreteFillColor 137
5.5.2 MarkerStyle 137
5.5.3 ReferenceLineModel 140
Part 2 Output Delivery System 143
Chapter 6 Important Concepts for Getting Started with ODS
and Java 145
6.1 Java Scriptlet Code 146
6.2 General JSP Structure 146
6.3 General JSP Requirements 148
6.4 Connecting and Data Extraction 148
6.5 A Few Last Notes about Data 151
Chapter 7 Creating Graphs 153
7.1 Types of Bar Charts 154
7.1.1 Horizontal Bar Charts 154
7.1.2 Vertical Bar Charts 155
7.2 Types of Pie Charts 156
7.2.1 Pie Charts 157
7.2.2 Donut Charts 158
7.2.3 Star Charts 159
7.3 Contour Plots 159
7.4 Types of Maps 160
7.4.1 Block Maps 160
7.4.2 Choropleth Maps 161
7.4.3 Prism Maps 162
7.4.4 Surface Maps 163
7.5 Types of Plots 163
7.5.1 Bubble Plots 164
7.5.2 Plots 165

7.6 Three-Dimensional Graphs 166
7.6.1 Scatter Plots 166
7.6.2 Surface Plots 167
Chapter 8 Parameters for Colors 169
8.1 ODS Parameters 170
8.1.1 Non-supported parameters 181
8.2 GOPTIONS 182
8.2.1 Non-supported options 186
8.3 PROC GCHART 186
8.3.1 Summary 192
8.3.2 Non-supported parameters 193
8.4 PROC GCONTOUR 193
8.4.1 Summary 197
8.5 PROC GMAP 197
8.5.1 Summary 199
8.6 PROC GPLOT 199
8.6.1 Summary 204
8.7 PROC G3D 204
8.7.1 Summary 205
8.7.2 Non-supported parameters 205
Chapter 9 Parameters for Text 207
9.1 ODS Parameters 208
9.1.1 Non-supported parameters 213
9.2 GOPTIONS 214
9.2.1 Non-supported parameters 217
9.3 PROC GCHART 217
9.3.1 Summary 225
9.3.2 Non-supported parameters 226
9.4 PROC GCONTOUR 227
9.4.1 Summary 231
9.5 PROC GMAP 232
9.5.1 Summary 234
9.6 PROC GPLOT 234
9.6.1 Summary 238

9.7 PROC G3D 239
9.7.1 Summary 240
Chapter 10 Other Parameters 241
10.1 PROC GCHART 242
10.1.1 Summary 264
10.1.2 Non-supported parameters 267
10.2 PROC GCONTOUR 268
10.2.1 Non-supported parameters 272
10.3 PROC GMAP 273
10.3.1 Summary 277
10.3.2 Non-supported parameters 278
10.4 PROC GPLOT 278
10.4.1 Summary 289
10.4.2 Non-supported parameters 289
10.5 PROC G3D 290
10.5.1 Summary 298
10.5.2 Non-supported parameters 298
Part 3 Putting It Together 299
Chapter 11 Final Reports 301
11.1 Report 1: Using SAS AppDev Studio 3 Tags 301
11.2 Report 2: Using ODS 307
11.3 Conclusions 310
Appendix A SAS/GRAPH Samples and WORK Data Sets 313
References 315
Index 317

SPSS : clementine 7.0用户手册（第三版）

2008-08-04 10:37:00

中文翻译的clementine使用手册,写得比较全面、详细。虽然clementine已经有更新的版本，但基本使用方法没有变。参考中文手册，比看英文的更容易上手些。推荐做数据挖掘的人可以参考一下。
【目录】
第1 章CLEMENTINE 概述.................... 12
1.1 启动...............12
1.1.1 安装Clementine...............................12
1.1.2 启动Clementine...............................14
1.2 CLEMENTINE 一览.....................................15
1.2.1 Clementine 界面...................................16
1.2.2 在Clementine 中使用鼠标..............18
1.2.3 利用快捷键......................................18
1.2.4 Clementine 中获得帮助.......................19
1.3 CLEMENTINE 选项设置.............................20
1.3.1 系统选项20
1.3.2 默认目录的设置..............................21
1.3.3 用户选项的设置..............................21
1.4 CLEMENTINE 自动化.................................25
第2 章CLEMENTINE 7.0 版本的新功能........................................ 26
2.1 欢迎...............26
2.2 新特征...........26
2.2.1 支持CRISP-DM...............................26
2.2.2 有关CLEM 表达式帮助.................28
2.2.3 界面友好性的增强..........................29
2.2.4 标准化功能......................................29
2.2.5 更强大的源节点..............................30
2.2.6 新图形...30
2.2.7 字段选择器......................................31
2.2.8 树形阅读器......................................32
2.2.9 批处理模式......................................32
2.2.10 技术的增强......................................33
2.3 从CLEMENTINE 6.5 以来的变化..............33
2.3.1 批处理模式......................................33
2.3.2 输出.......34
2.3.3 改进的脚本......................................34
2.3.4 更为灵活的超级节点......................34
2.3.5 改变数据储存..................................35
2.3.6 被要求的功能..................................35
2.3.7 兼容性问题......................................36
第3 章数据挖掘入门............................... 38
3.1 数据挖掘回顾38
3.2 机器学习技术38
3.2.1 神经网络38
3.2.2 规则归纳39
3.2.3 Kohonen 网络.......................................40
3.2.4 关联规则41
3.2.5 统计模型43
3.2.6 聚类模型43
3.3 潜在数据挖掘应用评估..........................44
3.3.1 数据是可以得到的吗？..................44
3.3.2 数据包含所需要了解的属性吗？..45
3.3.3 数据是否有噪声？..........................45
3.3.4 数据的数量够吗？..........................45
3.3.5 可以获得关于数据的专家知识吗？........................................45
3.4 数据挖掘的策略......................................45
3.4.1 CRISP －DM 过程模型........................46
3.5 小技巧...........47
3.5.1 归纳，神经网络，或统计模型？..47
3.5.2 数据均衡吗？..................................48
3.5.3 抽样.......48
3.5.4 异常的收集......................................48
第4 章构建数据流................................... 49
4.1 概要...............49
4.2 建立数据流（BUILDING DATA STREAM）.........................................49
4.2.1 节点的操作......................................50
4.2.2 数据流的操作..................................58
4.2.3 运行数据流......................................64
4.2.4 保存数据流......................................64
4.2.5 装载文件65
4.2.6 映射数据流......................................65
第5 章处理缺失值................................... 70
5.1 总论...............70
5.2 指定缺失值...70
5.3 处理缺失值...71
5.3.1 处理带缺失值的记录......................72
5.3.2 处理带缺失值的字段......................72
5.4 针对缺失值的CLEM 函数.....................73
5.4.1 关于删除记录的注意事项..............74
第6 章源节点. 75
6.1 概要...............75
6.2 变量文件节点（VARIABLE FILE NODE） 75
6.2.1 为变量文件节点设置选项（Setting Options for Variable File Node ）.............................76
6.3 固定文件节点（FIXED FILE NODE） ......77
6.3.1 为固定文件节点设置选项（Setting Options for the Fixed File Node ）...........................77
6.4 为文本区设置数据存储（SETTING DATA STORAGE FOR TEXT FIELDS） ...................................78
6.5 数据库节点（DATABASE NODE） ...........79
6.5.1 设置数据库节点选项（Setting Database Node Options ）......80
6.5.2 添加数据库连接（Adding a Database Connection ）..............80
6.5.3 选择数据表（Selecting a Database Table ）.............................81
6.5.4 数据库查询（Querying the Database ）...................................82
6.6 SPSS 导入节点（SPSS IMPORT NODE） 82
6.7 SAS 导入节点（SAS IMPORT NODE）....83
6.7.1 为SAS 导入节点设置选项(Setting Option for the SAS Import Node) ................................84
6.8 用户输入节点（USER INPUT NODE） .....84
6.8.1 为用户输入节点设置选项（Setting Options for the User Input Node ）...........................85
6.9 一般源节点条目（COMMON SOURCE NODE TABS） ........................87
6.9.1 在源节点中设置数据类型（Setting Data Type in the Source Node ）...............................87
6.9.2 在源节点处过滤字段......................89
第7 章记录操作节点............................... 91
7.1 记录操作概述91
7.2 选择节点（SELECT NODE） ....................91
7.3 抽样节点（SAMPLE NODE） ...................92
7.3.1 抽样节点选项..................................93
7.4 均衡节点(BALANCE NODE)......................93
7.4.1 均衡节点的设置选项......................94
7.5 聚合节点（AGGREGATE NODE）.............94
7.5.1 聚合节点的设置选项......................95
7.6 排序节点(SORT NODE) .............................96
7.7 合并节点（MERGE NODE） ....................97
7.7.1 指定合并方法和关键字段..............97
7.7.2 从合并节点过滤字段......................98
7.7.3 设置输入顺序并加上标签..............99
7.8 追加节点（APPEND NODE） .................100
7.8.1 设置追加选项................................101
7.9 区分节点.....101
第8 章字段操作节点............................. 102
8.1 总论.............102
8.2 类型节点（TYPE NODE）......................102
8.2.1 数据类型........................................103
8.2.2 什么是实例化？............................105
8.2.3 读取数据值....................................106
8.2.4 检查类型值....................................110
8.2.5 设定字段方向................................ 111
8.2.6 复制类属性....................................112
8.3 过滤节点(FILTER NODE) ........................112
8.3.1 设定过滤节点的选项....................113
8.4 导出节点(DERIVE NODE) .......................115
8.4.1 设置导出节点的基本选项............115
8.4.2 导出多重字段................................116
8.4.3 设置导出规则选项........................118
8.4.4 设置导出标记选项........................119
8.4.5 设置导出设置节点选项................120
8.4.6 设定导出状态选项........................121
8.4.7 设置导出计数选项........................122
8.4.8 设置导出条件选项........................123
8.5 填充节点.....124
8.5.1 用填充节点转换存储值................126
8.6 设置标记节点........................................126
8.6.1 设置标记节点的设置选项............127
8.7 历史节点.....128
8.7.1 历史节点的设置选项....................128
第9 章建立CLEM 表达式................... 130
9.1 什么是CLEM？ ....................................130
9.1.1 值及数据类型................................130
9.1.2 表达式及条件................................131
9.2 使用表达式构建器................................132
9.2.1 获取表达式构建器（accessing the expression builder ）.......132
9.2.2 构造表达式（creating expressions ）......................................133
9.2.3 选择函数（Selecting Functions ）.133
9.2.4 选择字段、参数以及全局变量（Selecting Fields ，Parameters ， and Global Variables ）
9.2.5 选择变量值（Selecting Values ）..134
9.2.6 检查CLEM 表达式（Checking CLEM Expressions ）...........135
9.3 CLEM 函数类型....................................135
9.4 CLEM 的常见用法(COMMON USES OF CLEM)...............................136
9.4.1 对字符串的操作（Working with Strings ）...........................136
9.4.2 处理空和缺失值（Handing Blanks and Missing Values ）.....137
9.4.3 处理数字（Working with Numbers ）......................................137
9.4.4 处理时间和日期（Working with Times and Dates ）..............137
第10 章图节点......................................... 139
10.1 概述.............139
10.1.1 层叠图表(Overlay Graphs)............139
10.1.2 3 －D 图像......................................141
10.1.3 动画效果(Animation).....................141
10.2 建立图(BUILDING GRAPHS) ..................142
10.2.1 为图表设定输出选项(Setting Output Options for Graphs) ....142
10.2.2 设置图外观选项(Setting Appearance Options for Graphs) ....142
10.3 使用图表.....144
10.3.1 一般图表窗口选项........................145
10.4 点图节点(PLOT NODE) ............................146
10.4.1 为点图节点设置选项（Setting Options for the Plot Node ）.148
10.4.2 使用点图(using a plot graph) ......150
10.5 多点图节点（MULTIPLOT NODE） .......153
10.5.1 为多点图节点设置选项（Setting Options for the Multiplot Node ）...............................153
10.5.2 使用一个多点图（Using a Multiplot Graph ）.......................154
10.6 分布节点（DISTRIBUTION NODE） .......155
10.6.1 设置分布节点选项（Setting Options for the Distribution Node ）..................................155
10.6.2 使用一个分布图（Using a Distribution Graph ）..................156
10.7 直方图节点（HISTOGRAM NODE）.......157
10.7.1 设置直方图节点更多选项（Setting Additional Options for the Histogram Node ）.......158
10.7.2 使用一个直方图（Using a Histogram Graph ）....................158
10.8 堆积图节点COLLECTION NODE.............161
10.8.1 设置堆积图节点的更多选项（Setting Additional Options for the Collection Node ）....162
10.8.2 堆积图的使用（Using a Collection Graph ）.........................162
10.9 WEB 图节点..164
10.9.1 设置Web 图节点选项（Setting Options for the Web Node ）165
10.9.2 设置Web 图节点的更多选项（Setting Additional Options for the Web Node ）.............166
10.9.3 Web 图节点的外观选项（Appearance Options for the Web Plot ）.................................167
10.9.4 Web 图像的使用（Using a Web Graph ）...............................168
10.10 评估图表节点（EVALUATION CHART NODE）...........................171
10.10.1 置评估图表节点选项（Setting Options for the Evaluation Chart Node ）..................173
10.10.2 读取模型评估的结果（Reading the Results of a Model Evaluation ）........................175
10.10.3 一个评估图表的使用（Using an Evaluation Chart ）.......176
第11 章建模节点..................................... 177
11.1 建模节点概述........................................177
11.1.1 建模节点字段选项........................177
11.2 神经网络节点........................................179
11.2.1 神经网络节点模型选项................180
11.2.2 神经网络节点的附加选项............182
11.2.3 神经网络节点高级选项——快速方法..................................184
11.2.4 神经网络节点高级选项——动态方法..................................184
11.2.5 神经网络节点高级选项——多重方法..................................185
11.2.6 神经网络节点高级选项——修剪方法..................................186
11.2.7 神经网络节点高级选项——RBFN 方法...............................187
11.2.8 神经网络节点高级选项——彻底修剪方法..........................188
11.2.9 神经网络节点学习比率................188
11.3 KOHENEN 节点.......................................188
11.3.1 Kohenen 节点模型选项................189
11.3.2 Kohenen 节点高级选项................190
11.4 C5.0 节点.....192
11.4.1 C5.0 节点模型选项.......................193
11.4.2 错误归类损失选项........................194
11.5 线性回归节点........................................195
11.5.1 线性回归节点模型选项................196
11.5.2 线性回归节点高级选项................197
11.5.3 线性回归节点单步选项................198
11.5.4 线性回归节点输出选项................198
11.6 广义规则归纳节点................................199
11.6.1 广义规则归纳节点模型选项........200
11.7 APRIORI 节点.........................................201
11.7.1 Apriori 节点模型选项..................201
11.7.2 Apriori 节点高级选项..................202
11.8 K-MEANS 节点.......................................204
11.8.1 K-Means 节点建模选项...............205
11.8.2 K-Means 节点高级选项...............206
11.9 逻辑斯谛回归节点................................206
11.9.1 逻辑斯谛回归节点模型选项........207
11.9.2 逻辑斯谛回归节点高级选项........208
11.9.3 逻辑斯谛回归节点收敛选项........209
11.9.4 逻辑斯谛回归输出选项................210
11.10 因子分析/主成分节点.......................211
11.10.1 因子分析/ 主成分节点模型选项.........................................212
11.10.2 因子分析/ 主成分节点高级选项.........................................213
11.10.3 因子分析/ 主成分节点旋转选项.........................................214
11.11 两步聚类节点....................................215
11.11.1 两步聚类型节点模型选项............216
11.12 分类回归树节点................................217
11.12.1 分类回归树节点模型选项........218
11.12.2 ??类回归树节点高级选项........218
11.12.3 分类回归树节点终止选项........220
11.12.4 分类回归树节点先验概率选项221
11.13 序列节点..222
11.13.1 序列节点字段选项....................223
11.13.2 序列节点模型选项....................225
11.13.3 序列节点高级选项....................226
第12 章输出节点..................................... 228
12.1 输出节点概述........................................228
12.2 使用输出.....228
12.3 输出浏览菜单........................................229
12.3.1 发布到Web ....................................230
12.4 输出节点输出条目................................230
12.5 表格节点.....231
12.5.1 表格节点设置条目........................232
12.5.2 表格节点格式条目........................232
12.5.3 表格浏览器....................................233
12.6 矩阵节点.....234
12.6.1 矩阵节点设置条目........................234
12.6.2 矩阵节点外观条目........................236
12.6.3 矩阵输出浏览器............................237
12.7 分析节点.....237
12.7.1 分析节点analysis 条目.................238
12.7.2 分析输出浏览器............................239
12.8 统计量节点..240
12.8.1 统计量节点设置条目....................241
12.8.2 统计量输出浏览器........................242
12.9 质量节点.....243
12.9.1 质量节点质量条目........................244
12.9.2 质量节点输出浏览器....................244
12.10 报告节点..246
12.10.1 报告节点模板条目....................246
12.10.2 报告节点输出浏览器................247
12.11 设置全局节点....................................248
12.11.1 设置全局节点设置条目............248
12.12 方案发布节点（SOLUTION PUBLISHER NODE） .........................249
12.12.1 为方案发布节点设置选项........250
12.13 数据库输出节点................................250
12.13.1 数据库节点输出条目................251
12.14 平面文件节点....................................252
12.14.1 平面文件输出条目....................252
12.15 SPSS 输出节点.................................253
12.15.1 SPSS 输出节点输出条目..............253
12.16 SAS 输出节点....................................254
12.16.1 SAS 输出节点输出条目................254
12.17 EXCEL 节点.........................................255
12.17.1 Excel 节点输出条目......................255
12.18 SPSS 程序节点.................................255
12.18.1 SPSS 程序节点语法条目..............256
12.18.2 SPSS 程序输出浏览器..................257
12.19 应用软件帮助....................................258
第13 章生成模型..................................... 259
13.1 生成模型概述........................................259
13.2 在生成模型选项板中利用生成模型进行操作...............................259
13.3 在数据流中使用生成模型....................261
13.4 使用生成模型浏览器............................261
13.5 生成网络节点........................................262
13.5.1 生成的神经网络总结条目............263
13.5.2 从神经网络中生成一个过滤节点264
13.6 生成KOHONEN 节点..............................264
13.6.1 生成的Kohonen 网络summary 条目.....................................265
13.7 生成的K-MEANS 节点...........................266
13.7.1 生成的K-Means 模型条目...........267
13.7.2 生成的K-Means 总结条目...........268
13.8 LOGISTIC 回归方程节点.........................268
13.8.1 Logistic 回归方程总结条目..........269
13.8.2 高级Logistic 回归输出.................271
13.9 线性回归方程节点................................272
13.9.1 线性回归等式总结条目................272
13.9.2 线性回归方程的高级输出............274
13.10 因子方程节点....................................275
13.10.1 因子方程模型条目....................275
13.10.2 因子方程总结条目....................276
13.10.3 因子方程高级输出....................278
13.11 未精练的规则模型............................279
13.11.1 未精练规则的模型条目............279
13.11.2 未精练规则的总结条目............280
13.11.3 生成规则集................................281
13.12 生成的规则集节点............................281
13.12.1 生成的规则集模型条目............282
13.12.2 生成的规则集总结条目............284
13.13 生成的决策树节点............................284
13.13.1 决策树模型条目........................285
13.13.2 决策树浏览条目........................288
13.13.3 决策树总结条目........................289
13.13.4 从决策树生成规则集................290
13.13.5 改进的C5.0 模型......................291
13.14 生成两步聚类节点............................291
13.14.1 生成的两步模型条目................292
13.14.2 生成的两步总结条目................293
13.14.3 生成的序列规则节点................293
13.14.4 序列规则模型条目....................294
13.14.5 序列规则的总结条目................296
13.14.6 从序列规则节点生成规则超级节点..................................297
第14 章输出模型..................................... 299
14.1 模型输出概论........................................299
14.1.1 模型的输出....................................299
14.2 PMML 输出.300
14.3 C 代码输出..300
14.3.1 输出C5.0 决策树和规则集..........300
14.3.2 输出网络（Exporting Nets ）........301
14.3.3 输出径向基函数网络网络（Exporting Radial Basis Function (RBF) Nets ）.................303
14.3.4 输出Kohonen 网络........................305
14.3.5 输出K-Means 模型（Exporting K-Means Models ）.............307
14.3.6 字段名（Field Names ）................308
14.3.7 模型输出的错误代码（Error Codes for Model Export ）......309
第15 章超级节点..................................... 310
15.1 概要.............310
15.2 超级节点类型（TYPES OF SUPERNODES） .....................................310
15.3 创建一个超级节点（CREATING A SUPERNODE） ..........................312
15.3.1 嵌套超级节点（Nesting SuperNodes ）..................................314
15.3.2 有效超级节点举例（Examples of Valid SuperNodes ）.........314
15.3.3 无效超级节点举例（Examples of Invalid SuperNodes ）......315
15.4 编辑超级节点（EDITING A SUPERNODE） .....................................316
15.4.1 修改超级节点的类型（Modifying SuperNode Type ）...........317
15.4.2 注释和重命名超级节点（Annotating and Renaming SuperNodes ）..............................317
15.4.3 超级节点参数（SuperNode Parameters ）.............................318
15.4.4 超级节点和缓存（SuperNodes and Caching ）......................321
15.4.5 超级节点和脚本（SuperNodes and Scripting ）....................322
15.5 保存并装载超级节点（SAVING AND LOADING SUPERNODES） ....323
第16 章建立项目和报告......................... 324
16.1 项目介绍（INTRODUCTION TO PROJECTS）.....................................324
CRISP-DM 观察方式....................................325
Classes 观察窗口（Classes View ）..............325
16.2 建立项目（BUILDING A PROJECT）.......326
16.2.1 创建新项目（Creating a New Project ）................................326
16.2.2 添加到项目中（Adding to a Project ）...................................326
16.2.3 设置项目属性（Setting Project Properties ）.........................328
16.2.4 评注项目（Annotating a Project ）.........................................328
16.2.5 对象属性（Object Properties ）....330
16.2.6 关闭项目（Closing a Project ）....330
16.3 创建报告（BUILDING A REPORT）........330
16.3.1 生成报告（Generating Reports ）.331
16.3.2 保存和输出报告（Saving and Exporting Reports ）..............332
第17 章批处理模式（BATCH MODE EXECUTION）................. 335
17.1 批处理模式一览（INTRODUCTION TO BATCH MODE） ..................335
17.2 在批处理模式下工作（WORKING IN BATCH MODE） ...................335
17.2.1 软件调用（Invoking the Software ）.......................................335
17.2.2 使用命令行参数（Using Command Line Arguments ）.........336
17.2.3 批处理模式日志文件（Batch Mode Log Files ）...................336
17.2.4 批处理模式中的脚本编程（Scripting in Batch Mode ）.......336
17.2.5 在批处理模式中使用参数（Using Parameters in Batch Mode ）...................................337
17.2.6 在批处理模式下输出（Working with Output in Batch Mode ）......................................338
第18 章CLEMENTINE 中的脚本编程... 339
18.1 脚本编程介绍........................................339
18.1.1 脚本类型........................................339
18.2 在用户界面上进行脚本编程.................340
18.2.1 在流中使用脚本............................340
18.2.2 在超级节点中使用脚本................342
18.2.3 使用独立脚本................................343
18.3 以批处理模式编写脚本........................345
第19 章CLEMENTINE 外部模块接口.. 346
19.1 介绍.............346
19.2 运行CEMI ..346
19.3 系统体系结构........................................346
19.4 规范说明文件........................................347
19.4.1 参数.....348
19.4.2 外部程序........................................348
19.4.3 命令行选项....................................348
19.4.4 编辑对话框....................................348
19.4.5 输入和输出字段............................349
19.4.6 输入和输出文件............................349
19.4.7 元文件..349
19.4.8 结果.....350
19.4.9 返回代码........................................350
19.5 限制.............350
19.6 规范说明文件示例................................350
19.6.1 节点说明........................................351
19.6.2 核心说明........................................351
19.6.3 参数.....351
19.6.4 执行.....352
19.6.5 选项.....352
19.6.6 控件.....353
19.6.7 输出字段........................................354
19.6.8 输出数据........................................354
19.6.9 返回代码........................................354
19.6.10 完整的规范文件........................355
19.7 CEMI 节点管理.....................................357
19.7.1 增加CEMI 节点............................358
19.7.2 清除CEMI 节点............................358
19.8 编写外部程序的技巧............................358
第20 章应用示例..................................... 360
20.1 概况.............360
20.2 状态监测示例........................................360
20.2.1 审视数据........................................361
20.2.2 数据准备........................................363
20.2.3 学习.....364
20.2.4 测试.....365
20.3 欺诈稽查示例........................................366
20.3.1 数据获取........................................366
20.3.2 数据探索........................................367
20.3.3 训练神经网络................................370
20.3.4 总结.....372
20.4 零售业示例..372
20.4.1 数据审核........................................373
20.4.2 学习和测试....................................376
20.5 市场购物篮分析示例............................377
20.5.1 获取数据........................................377
20.5.2 购物内容关联分析........................378
20.5.3 客户细分........................................381
20.5.4 总结.....383

数据库基础与应用实践教程

2008-06-03 22:06:36

容提要：
本书是与作者编写的《数据库基础与应用教程》配套的实验教材。全书共包括3部分内容：上机实验指导、习题选解和数据库应用系统案例。上机实验指导部分包括16个实验，实验内容与课堂教学紧密结合，通过有针对性的上机实验，可以帮助读者更好地掌握Visual FoxPr0数据库的操作和应用方法。习题选解部分是为了帮助读者进行课外练习而编写的，对于准备参加各种计算机考试的读者来说，这部分内容是很好的辅导材料。数据库应用系统案例是为培养读者的数据库应用系统开发能力而编写的，这些案例将对读者进行系统开发起到示范作用。
本书集实验、习题和案例于一体，内容丰富，实用性强，既可作为高等院校数据库应用课程的实验教材，又可供社会各类计算机应用人员和准备参加各类计算机等级考试的读者参考。

目录：
第1部分　上机实验指导
　实验1　Visual FoxPr0的环境与运算
　实验2　表的建立与维护
　实验3　表的排序、索引与统计
　实验4　多表操作
　实验5　数据库的操作
　实验6　结构化查询语言SQL
　实验7　查询与视图
　实验8　顺序结构与选择结构
　实验9　循环结构
　实验10　子程序
　实验11　类与对象的设计
　实验12　表单的设计
　实验13　表单的应用
　实验14　菜单的设计与应用
　实验15　报表与标签的设计
　实验16　数据库应用系统的开发
第2部分　习题选解
　1　数据库系统概论
一、选择题
　二、填空题
三、参考答案
　2　Visual FoxPr0基础
一、选择题
二、填空题
三、参考答案
　3　表的建立与操作
一、选择题
　二、填空题
　三、参考答案
　4　数据库的建立与操作
一、选择题
　二、填空题
　三、参考答案
　5　结构化查询语言SQL
一、选择题
二、填空题
三、操作题
四、参考答案
　6　查询与视图
一、选择题
　二、填空题
　三、参考答案
　7　结构化程序设计
一、选择题
二、阅读程序题
三、程序填空题
四、程序设计题
五、参考答案
　8　表单设计与应用
　　一、选择题
　　二、填空题
　　三、程序填空题
　　四、操作题
　　五、参考答案
　9　菜单设计
　　一、选择题
　　二、填空题
　　三、操作题
　　四、参考答案
　10　报表与标签设计
　　一、选择题
　　二、填空题
　　三、操作题
　　四、参考答案
第3部分　数据库应用系统案例
　1　工资计算与管理系统
　　一、系统需求分析
　　二、系统设计
　　三、系统的实现
　2　图书馆管理信息系统
　　一、系统需求分析
　　二、系统设计
　　三、系统实现
　　四、存在的问题及改进的办法
　3　旅游信息管理系统
　　一、系统分析
　　二、系统设计
　　三、系统实现方案
　　四、系统程序设计
　　五、系统调试及运行
主要参考文献

Building PDA Databases For Wireless And Mobile Development

2008-05-20 12:39:20

Table of Contents
Building PDA Databases for Wireless and Mobile Development..................................................................1
IntroductionAn Introduction to Wireless and Mobile Applications..............................................................4
About This Book....................................................................................................................................5
Is This Book for You?............................................................................................................................6
Covered Material...................................................................................................................................6
Chapter 1: Introduction to PDAs.....................................................................................................................8
The Basics..............................................................................................................................................8
Portable Wireless Evolution...................................................................................................................9
What Is WAP?.................................................................................................................................9
WAP Evolution...............................................................................................................................9
PDA Evolution..............................................................................................................................11
PDA Environment................................................................................................................................12
Devices..........................................................................................................................................12
Connectivity..................................................................................................................................14
Final Thoughts.....................................................................................................................................17
The Relational Database and Its Components......................................................................................17
Tables............................................................................................................................................18
Primary Keys.................................................................................................................................19
Indexes...........................................................................................................................................20
Referential Integrity (Foreign Keys)..............................................................................................21
Joins...............................................................................................................................................22
Cursors...........................................................................................................................................23
SQL...............................................................................................................................................23
Security..........................................................................................................................................24
Database Administration......................................................................................................................25
Backups.........................................................................................................................................26
PDA Database Considerations.......................................................................................................26
Final Thoughts.....................................................................................................................................27
Chapter 3: Client?Server Architecture.........................................................................................................28
Client?Server History..........................................................................................................................28
What Is Client?Server?........................................................................................................................29
Fat versus Thin.....................................................................................................................................31
Tiers.....................................................................................................................................................32
Front End.............................................................................................................................................34
Security................................................................................................................................................35
PDA Units............................................................................................................................................35
Final Thoughts.....................................................................................................................................36
Chapter 4: Data Warehousing.......................................................................................................................37
What Is a Data Warehouse?..................................................................................................................37
Granularity.....................................................................................................................................38
Organized Structures.....................................................................................................................38
Architecture..........................................................................................................................................39
Source............................................................................................................................................39
ETL................................................................................................................................................40
Repository.....................................................................................................................................40
Data Marts.....................................................................................................................................41
i
Table of Contents
Chapter 4: Data Warehousing
PDA Data Warehousing.......................................................................................................................42
Data Stores....................................................................................................................................42
PDA Source...................................................................................................................................43
PDA Empowerment.............................................................................................................................44
Final Thoughts.....................................................................................................................................44
Chapter 5: Palm..............................................................................................................................................45
Overview..............................................................................................................................................45
History.................................................................................................................................................45
Overview..............................................................................................................................................47
Physical Units......................................................................................................................................49
Devices..........................................................................................................................................49
Cradles...........................................................................................................................................49
M500 Unit Specs...........................................................................................................................49
Graffiti..................................................................................................................................................51
Palm Desktop.......................................................................................................................................53
HotSync...............................................................................................................................................56
Beaming...............................................................................................................................................58
Palm Emulator.....................................................................................................................................58
Final Thoughts.....................................................................................................................................60
Chapter 6: Pocket PC.....................................................................................................................................61
Overview..............................................................................................................................................61
Physical Units......................................................................................................................................62
Device Comparison.......................................................................................................................65
Special Units..................................................................................................................................65
Compaq iPAQ H3870 Unit Specs..................................................................................................65
Software...............................................................................................................................................67
Microsoft ActiveSync..........................................................................................................................68
Beaming...............................................................................................................................................75
Final Thoughts.....................................................................................................................................76
Chapter 7: Mobile Application Development Tools.....................................................................................77
Microsoft eMbedded Visual Basic........................................................................................................77
AppForge 2.1.1....................................................................................................................................79
IBM Everyplace Mobile Application Builder 7.2.1..............................................................................80
CASL IDE............................................................................................................................................83
PenRight! MobileBuilder.....................................................................................................................85
DBArtisan............................................................................................................................................87
Final Thoughts.....................................................................................................................................87
Chapter 8: Palm's Database...........................................................................................................................88
Overview..............................................................................................................................................88
PDB Example: Fugitive Application....................................................................................................88
PDB Database Components...........................................................................................................90
AppForge 2.1 Setup and Installation....................................................................................................92
PDB Example: Fugitive Application....................................................................................................96
Final Thoughts...................................................................................................................................113
ii
Table of Contents
Chapter 9: Microsoft....................................................................................................................................114
Overview............................................................................................................................................114
SQL Server 2000 CE Edition..............................................................................................................115
Installing Windows SQL 2000 CE Edition..................................................................................116
File Locations....................................................................................................................................118
Development System....................................................................................................................118
Internet Information Services System..........................................................................................118
ActiveSync System.......................................................................................................................119
Windows CE Device....................................................................................................................119
Replication.........................................................................................................................................119
Sample ApplicationSurveys...............................................................................................................120
Create the Survey Database..........................................................................................................121
Replication Setup.........................................................................................................................124
Creating the Survey Application..................................................................................................131
Final Thoughts...................................................................................................................................145
Chapter 10: Sybase.......................................................................................................................................146
Highlights...........................................................................................................................................146
Overview............................................................................................................................................146
SQL Anywhere Studio........................................................................................................................147
Relational Database Components.................................................................................................148
Data Synchronization and Replication.........................................................................................148
Database Administration Tools....................................................................................................148
Embedded Database Architecture.......................................................................................................149
Client?Server Architecture.................................................................................................................150
Adaptive Server Anywhere.................................................................................................................151
Overview.....................................................................................................................................151
DBMS Specifics..........................................................................................................................151
UltraLite.............................................................................................................................................153
Overview.....................................................................................................................................153
UltraLite Architecture..................................................................................................................153
UltraLite Features........................................................................................................................155
MobiLink...........................................................................................................................................156
Overview.....................................................................................................................................156
Consolidated Database.................................................................................................................156
Central Database Subset...............................................................................................................158
MobiLink Synchronization Server...............................................................................................158
MobiLink Synchronization Process.............................................................................................159
Mobile Synchronization System..................................................................................................160
MobiLink Quick Start..................................................................................................................161
Vineyards Application.......................................................................................................................163
Flow Chart...................................................................................................................................163
ASA Database and Tables............................................................................................................164
AppForge Conduit........................................................................................................................167
The Application...........................................................................................................................173
Final Thoughts...................................................................................................................................190
Chapter 11: IBM...........................................................................................................................................192
Highlights...........................................................................................................................................192
Overview............................................................................................................................................192
iii
Table of Contents
Chapter 11: IBM
System Tables....................................................................................................................................194
Limitations.........................................................................................................................................195
Installation on the Windows Workstation...........................................................................................196
Installation on Mobile Device.............................................................................................................197
Development Tools............................................................................................................................198
Airplane Tester Application................................................................................................................198
Create Testers Tables...................................................................................................................199
Main Application.........................................................................................................................207
Data Synchronization and Replication................................................................................................218
Final Thoughts...................................................................................................................................221
Appendix A: Palm Conduits........................................................................................................................222
Appendix B: Microsoft Publication Wizard Script....................................................................................225
Appendix C: DB2 CLI/ODBC Functions....................................................................................................233
Appendix D: Sybase Glossary.............................................................................................................234
C?U..............................................................................................................................................234
Acronyms........................................................................................................................................................236
iv

Bioinformatics : Databases and Systems

2008-05-19 22:41:23

INTRODUCTION
Stanley Letovsky
Bioinformatics is a field that has exploded into the awareness of biomedical,
pharmaceutical and agricultural researchers in the last few years, in parallel with the
equally new field of genomics. The central idea of genomics, first articulated by a
few visionary biologists and funding officials at the US Department of Energy and
National Institutes of Health in the 1980’s, was to scale up the laboratory techniques
of molecular biology, and to bring to biology a degree of completeness that seemed
revolutionary at the time. Rather than mapping one gene at a time, people began to
develop whole genome maps at specified marker densities. Rather than sequencing a
gene at a time, they proposed to sequence the entire human genome, a project one
hundred thousand times larger. Although the goal of a complete sequence of the 3000
megabase human genome remains in the future1, the significance of this vision has
already been demonstrated many times over. Major milestones to date include the
first complete genomic sequencing in 1995 of the 2 MB genome of the bacterium
Haemophilus influenzae [2] by a group at the Institute for Genomic Research
(TIGR), followed by some dozen other bacterial species since then; of the first
single-celled eukaryote in 1997, the budding yeast Saccharomyces cereviseae, with a
genome size of 12 MB, by an international consortium of academic laboratories [3],
and the completion in 1998 of the first multicellular eukaryote, the nematode worm
Caenorhabditis elegans, with a genome size of about 100MB [4]. Projects are well
under way to produce the genomic sequences of the fruitfly Drosophila melanogaster
[5] and the mustard weed Arabidopsis thaliana [6], important genetic model
organisms for the animal and plant kingdoms, respectively. Discussion is under way
on a public project to sequence the mouse, which is a crucial model organism for the
mammals.
In addition to genome sequencing, a number of other large-scale
technologies have been developed to shed new light on the structure and function of
organismal genomes. These include EST sequencing, which allows gene RNA
products to be observed more directly than genomic sequencing permits;
transcriptional profiling methods such as microchip-based hybridization arrays, that
allow measurement of cells’ gene expression levels; yeast 2-hybrid systems to allow
the construction of protein interaction maps; radiation-hybrid mapping which allow
genome maps to be built (in some species) without reliance on cumbersome natural
recombination; and high-throughput screening methods which allow the biological
effects of large small-molecule compound libraries to be rapidly assessed. If
genomics at present is using tomorrow’s technologies today, often before all the
kinks have been worked out, numerous groups are hard at work on the technologies
of the day after tomorrow. Examples include protein profiling, or proteomics, which
surveys the protein content of cells and tissues using high-resolution mass
spectrometry; metabolic profiling, which measures the small molecule content of
tissues; cheap polymorphism detection methods; and nanofabricated laboratory-on-achip
technologies that may provide the elusive increases in speed and reductions in
cost that have long been sought for “conventional” genomic technologies such as
automated sequencing.
It is against the backdrop of this breakneck technology development and
mass production of genomic data that the field of bioinformatics emerged. People
had of course been applying computers to biological data for years before the term
was coined, and most of the common algorithms for biological sequence comparison
had been invented by 1980. But it was not until the mid-1990’s that the field acquired
a name, and suddenly became respectable, even fashionable. By 1996 it seemed that
every other issue of Science contained an article bemoaning the desperate shortage of
bioinformaticians in academic and industrial labs (e.g. [ 141).
A crucial parallel development in the larger culture that coincided with the
emergence of genomics and bioinformatics was the explosion of the Worldwide
Web. Vindicating, perhaps, Marshall MacLuhan’s cryptic insight that “the medium is
the message” (or “mass age”), the Web has inserted itself into discipline after
discipline, business after business, unleashing expanding ripples of transformation.
Indeed the Web is one of the few technologies that are developing as fast as
genomics, but the connection between them runs deeper than that. The Web turns out
to be a nearly ideal vehicle for delivering genomic data to the scientific community; it
is hard to imagine what bioinformatics would look like without it.
So what is bioinformatics? Definitions vary with the users of word; related
terms like computational biology are held to be synonyms by some, and by others to
reflect subtle distinctions. In practical terms there are some important distinctions to
be made between the tasks of developing algorithms, of programming databases, and
of curating database content. Computational biology algorithms for sequence
comparison, sequence assembly, sequence classification, motif induction and
recognition, and protein structure prediction have been the subject of several recent
books [7-13] whereas the database system-building and content curation aspects have
received less treatment2. These are perhaps the less glamorous aspects of the field,
more lore than art, but these are also the areas where there seems to be a great hunger
for wisdom. Where algorithms tend to get implemented, packaged and shared as
black boxes, systems get built over and over in different establishments, and people
facing the same problems for the first time are always peppering their more
experienced counterparts with questions like “did you use approach/product/standard
X in your project? Was it any good? How do you keep the data up to date? How do
you enforce content quality?” This book was conceived as a resource for people
asking such questions, whose numbers seem to be doubling every six months at
present. It is not possible to give definite answers to these sorts of questions – yes
you should or no you shouldn’t use ACEDB or CORBA or OPM or whatever. The
software changes from month to month, the problems change, the options change.
Today’s technological rising star may be tomorrow’s horror story, and vice versa.
Even the insights derived from bitter experience can be questionable – did you really
diagnose the problem correctly, and if you build the next system the way you now
think you should have built the last one, will the result really be better or will you
simply encounter a different, equally painful set of tradeoffs? Nonetheless experience
is better than no experience, so I asked the contributors to this volume to include in
their articles lessons learned from developing their systems, and to write down their
thoughts on how they might do things differently -- or similarly -- if they were doing
it again.
The contributors represent what I hope will be an interesting, albeit
incomplete, sample of some of the most exciting work being done in bioinformatics
today. The articles are somewhat arbitrarily divided into two sections: Databases and
Software. The intent was that articles that focused more on content would fall into the
former category, while articles that focused on technology would fall into the latter,
but there were a number of borderline cases. My hope is that this collection will be of
interest to readers who have arrived at the interdisciplinary world of bioinformatics
either from the biology side or the computational side (as well as those more distant
migrants from literature, history, business, etc.). The database articles may be more
intelligible to readers with more of a biology background, and the software articles to
readers with more software engineering; hopefully there is something to interest (and
confuse) just about everyone.
The articles in the Database section represent some of the established (or in
some cases recently disestablished!) citizens of the database world, as well some
promising new efforts. The first few articles describe systems focused on the
molecular level; these are mostly multispecies, comparative systems. Karl Sirotkin of
NCBI describes some of the software underpinnings of Entrez, the most widely used
molecular biology resource. The article on HOVERGEN by Duret et al describes an
interesting new approach to integrating phylogenetic and coding sequence data into
an organized whole. Several articles focus on the fast-developing area of metabolic
and regulatory pathway databases, including those by Overbeek et al on WIT,
Kanehisa on KEGG, and Karp and Riley on EcoCyc.
The remaining articles in this section describe primarily databases organized
around organisms rather than molecules. Alan Scott describes the extensive
literature-based curation process used to maintain the high quality standards of
OMIM, the fundamental resource on human genetic disease. My own article looks at
methods of integrating maps in the erstwhile human Genome Database (GDB).
Cooper et al describe their database of human mutations, an early entry in the
increasingly important field of variation databases.
The article by Nadkarni et al provides a link to the developing field of
neuroinformatics, which is concerned with databases of such neuroscience data such
as structural (MR or CT) or functional (PET, fMRI) images of the brain, histological
slices, EEG and MEG data, cellular and network models, single cell recordings, and
so on. [15]. This article is included not only as a representative of neuroinformatic
work, but because it is one of the few current neuroinformatics efforts that links the
molecular scale of bioinformatics to the neurophysiological scale, since it addresses
the physiology of olfaction from the receptor sequences up to cellular and network
physiology.
Eppig et al describe the Mouse Genome Database (MGD) and its companion
system, the mouse Gene Expression Database (GXD). One of the key challenges for
the next generation of databases is to begin to span the levels of organization between
genotype and phenotype, where the processes of development and physiology reside.
Baldock et al describe an anatomical atlas of the mouse suitable for representing
spatiotemporal patterns of gene expression; the Edinburgh (Baldock et al) and
Jackson Laboratory (Eppig et al) projects are collaborating to link the genetic and
spatial databases together. The plant kingdom, which has recently experienced a
rapid acceleration of genomic scrutiny in both the private and public sectors, is
represented in articles on MaizeDB by Polacco and Coe and on the USDA’s
Agricultural Genome Information System by Beckstrom-Sternberg and Jamison.
Gelbart et al describe the rich integration of genomic and phenotypic data on
Drosophila in Flybase. Mary Berlyn describes the E.coli Genetic Stock Center
Database, which provides query-by-genotype access to the stock center’s extensive
collection of mutant strains.
The Software section contains a number of articles that address one or
another aspect of the problem of integrating data from heterogenous sources. There
are two common ways to achieve such integration: federation, in which the data
continue to reside in separate databases but a software layer makes them act as a
single integrated collection, and physical integration, often called warehousing, in
which the data are combined into a single repository for querying purposes. Both
approaches involve transforming the data into a common format; federation does the
transformation at query time, whereas warehousing does it as a preprocessing step.
One consequence of this difference is that warehouses are more difficult to keep
current as the underlying databases are updated. The choice of federation vs.
warehousing has performance implications as well, though they are not always easy
to predict. A warehouse can map in a straightforward way to a DBMS product, and
make full use of the tuning and optimization capabilities of that product. Federated
systems must pay the price of translating queries at run-time, possibly doing
unoptimized distributed joins of query fragments across multiple databases, and
converting data into the standard form. It is also possible for federated systems to
gain performance by distributing queries across multiple processors in parallel,
though such gains are rare in practice.
The OPM system, described in the article by Markowitz et al, uses a
middleware layer to impose a uniform object-oriented data model3 on a potentially
heterogeneous set of back-end databases. Davidson et al’s BioKleisli takes a similar
approach but uses as its common data model a model adopted from logic
programming which is similar to the relational model but more powerful.
The SRS system described by Carter et al occupies an interesting middle
ground between federation and warehousing. In SRS the datasets are warehoused in a
single computer for searching, but remain organized in their original formats. New
databases are added to the warehouse by supplying parsers for their flat-file formats;
the files themselves are unaffected, which makes updating an SRS system uniquely
simple compared to most warehouse designs.
The Biology Workbench project exemplifies another approach to data
integration made possible by the Web. It does not physically bring the data together
like SRS, nor does it create a virtual unified database like BioKleisli or the OPM
multidatabase capability. Instead, it integrates at the level of the front end by
providing a thin veneer of user interface which provides access to a number of
capabilities on the Web. A similar concept is employed by the BCM Search Launcher
[16].
A key challenge in bioinformatics software development is the need to
continuously evolve software systems to incorporate or adapt to new technologies
while maintaining compatibility with existing (legacy) systems. Traditional software
development practice has been described in terms of a “waterfall” model, in which
development progresses continuously “downstream” from requirements analysis to
design to implementation. This model provides little guidance to bioinformatics
developers, whose task more closely resembles that of an auto mechanic trying to
redesign a car while driving it. The rapid prototyping model, in which systems are
built by successive approximation from crude first attempts, comes closer to the
mark, but still assumes the luxury of an extended prototyping phase. The componentbased
design model, in which systems can be quickly assembled from reusable
components, is one that many in bioinformatics are pinning their hopes on. Jungfer et
al advocate the use of CORBA, an industry standard for designing distributed objectoriented
software systems, which has been adopted at the European Bioinformatics
Institute and elsewhere as a middleware layer to handle communication between back
end databases and front-end viewers and analysis tools. In contrast to OPM and
BioKleisli, CORBA does not so much offer a standard data model as provide a
mechanism for isolating system components from the design constraints that might be
imposed by choosing particular data models. The Biowidgets article by
Crabtree et al describes an approach to modular software development for
bioinformatics visualization. Biowidgets represents an attempt to apply that modular
design philosophy to the problem of data visualization.
The ACE database manager, described by Jean and Danielle Thierry-Mieg,
is the database kernel of the ACEDB system developed by Jean Thierry-Mieg and
Richard Durbin for the C.elegans genomic database, and subsequently reused widely
by many other projects. The tremendous success of ACEDB over the years can be
attributed to a number of factors, including its biologist-friendly user interface, the
ease with which data can be entered into it, the ease with which its schema can be
modified, the ease with which new visualization and analysis routines can be added
to it, the extensive genomics knowledge incorporated into its standard schema and
software, and its price (free!). At the core of the system is a somewhat non-standard
object-oriented DBMS which over a reasonably wide range of database sizes can
outperform most commercial relational databases at tasks such as retrieving an object
detail view, pulling up annotated sequence, or displaying a genetic map. It is
heartening, in an era when DBMS development has been taken over by large
corporations wielding enormous programming teams, to see that a tiny team of
talented individuals can still write a system which outperforms the commercial
products in many respects.
Laboratory information management systems (LIMS) are a species of
software remote from the experience of many bioinformatics practitioners, for whom
data are something that automatically appear in databases. Those of us who have had
occasion to wander into the more upstream regions of the data production process
encounter a world of robots, sequencing machines, bench biologists, pipettes and 96-
well plates. This world turns out to be full of interesting and exotic software
engineering challenges which are not well served by the current generation of
commercial solutions. Goodman et al present an elegant and general approach to the
problem of laboratory process workflow which they developed for use in the
Whitehead Genome Sequencing Center.
The articles in this book constitute a very incomplete sample of the
interesting systems out there. Notable gaps include databases for such important
model organisms as yeast, C.elegans and Arabidopsis as well as a number of
microbial databases; databases on protein sequences, families, and 3D structures;
expression profile databases, and transcription factor and promoter databases.
Starting points for finding such resources include [ 17,18].
One final note: in keeping with the rapid pace of change in this field, many
of the authors are no longer at the institutions where the work was performed, and in
some cases the addresses shown are out of date. During the period when this book
was being written (1997 -98), a number of the authors (myself, Markowitz et al, Karp,
Etzold) moved from public sector to private sector positions, and several of the
systems described (OPM, BioKleisli, EcoCyc, SRS, WIT, EBI-CORBA) went from
research systems to commercial products.
I would like to express my thanks to the authors for their contributions, and to
Anita Tilotta, Mary Panarelli and Cristina Carandang for their assistance in the
preparation of this book.

TABLE OF CONTENTS
INTRODUCTION ........... 1
Stanley Letovsky

DATABASES
1.NCBI: INTEGRATED DATA FOR MOLECULAR BIOLOGY RESEARCH ................. 11
Karl Sirotkin
2.HOVERGEN: COMPARATIVE ANALYSIS OF HOMOLOGOUS VERTEBRATE GENES ........ 21
Laurent Duret, Guy Perri‘ere and Manolo Gouy
3.WIT/WIT2: METABOLIC RECONSTRUCTION SYSTEMS ........................... 37
Ross Overbeek, Niels Larsen, Natalia Maltsev, Gordon D. Pusch, and
Evgeni Selkov
4.ECOCYC: THERESOURCE AND THE LESSONS LEARNED .......................... 47
Peter D. Karp and Monica Riley
5.KEGG: FROM GENES TO BIOCHEMICAL PATHWAYS ............................. 63
Minoru Kanehisa
6.OMIM: ONLINE MENDELIAN INHERITANCE IN MAN ............................ 77
Alan F. Scott, Joanna Amberger, Brandon Brylawski and Victor A.
McKusick
7.GDB: INTEGRATING GENOMIC MAPS ........................................ 85
Stanley Letovsky
8.HGMD: THE HUMAN GENE MUTATION DATABASE ............................... 99
Michael Krawczak, Edward V. Ball, Peter Stenson and David N. Cooper
9.SENSELAB: MODELING HETEROGENOUS DATA ON THE NERVOUS SYSTEM .......... 105
Prakash Nadkarni, Jason Mirsky, Emmanouil Skoufos, Matthew Healy,
Michael Hines, Perry Miller and Gordon Shepherd
10.THE MOUSE GENOME DATABASE AND THE GENE EXPRESSION DATABASE:GENOTYPE
TO PHENOTYPE ....................................................... 119
Janan T. Eppig, Joel E. Richardson, Judith A. Blake, Muriel T. Davisson,
James A. Kadin, and Martin Ringwald
11.THE EDINBURGH MOUSE ATLAS: BASIC STRUCTURE AND INFORMATICS ......... 129
Richard A Baldock, Christophe Dubreuil, Bill Hill and Duncan Davidson
12.FLYBASE: GENOMIC AND POST-GENOMIC VIEWPOINTS ....................... 141
The FlyBase Consortium
13.MAIZEDB: THE MAIZE GENOME DATABASE ................................. 151
Mary Polacco and Ed Coe
14.AGIS: USING THE AGRICULTURAL GENOME INFORMATION SYSTEM ............. 163
Stephen M. Beckstrom-Sternberg and D. Curtis Jamison
15.CGSC: THE E.COLI GENETIC STOCK CENTER DATABASE ..................... 175
Mary K.B. Berlyn

SYSTEMS
16.OPM: OBJECT-PROTOCOLMODEL DATAMANAGEMENT TOOLS‘97 .................. 187
Victor M. Markowitz, I-Min A. Chen, Anthony S. Kosky, and Ernest Szeto
17.BIOKLEISLI: INTEGRATING BIOMEDICAL DATA AND ANALYSIS PACKAGES ...... 201
Susan B. Davidson, O. Peter Buneman, Jonathan Crabtree, Val Tannen,
G. Christian Overton and Limsoon Wong
18.SRS: ANALYZING AND USING DATA FROM HETEROGENOUS TEXTUAL DATABANKS .. 213
Phil Carter, Thierry Coupaye, David P. Kreil, and Thure Etzold
19.BIOLOGY WORKBENCH: A COMPUTING AND ANALYSIS ENVIRONMENT FOR THE
BIOLOGICAL SCIENCES ................................................ 233
Roger Unwin, James Fenton. Mark Whitsitt, Curt Jamison, Mark Stupar,
Eric Jakobsson and Shankar Subramaniam
20.EBI: CORBA AND THE EBI DATABASES ................................... 245
Kim Jungfer, Graham Cameron and Tomas Flores
21.BIOWIDGETS: REUSABLE VISUALIZATION COMPONENTS FOR BIOINFORMATICS ... 255
Jonathan Crabtree, Steve Fischer, Mark Gibson and G. Christian Overton
22.ACEDB:THE ACE DATABASEMANAGER ...................................... 265
Jean Thierry-Mieg, Danielle Thierry-Mieg and Lincoln Stein
23.LABBASE: DATA ANDWORKFLOWMANAGEMENT FOR LARGE SCALE BIOLOGICAL
RESEARCH ........................................................... 279
Nathan Goodman, Steve Rozen, and Lincoln Stein
INDEX ................................................................. 293

Data Mining in Finance : Advances in Relational and Hybrid Methods

2008-05-14 22:15:48

PREFACE
The new generation of computing techniques collectively called data
mining methods are now applied to stock market analysis, predictions, and
other financial applications. In this book we discuss the relative merits of
these methods for financial modeling and present a comprehensive survey of
current capabilities of these methods in financial analysis.
The focus is on the specific and highly topical issue of adaptive linear
and non-linear “mining” of financial data. Topics are progressively developed.
First, we examine the distinction between the use of such methods as
ARIMA, neural networks, decision trees, Markov chains, hybrid knowledge-
based neural networks, and hybrid relational methods. Later, we focus
on examining financial time series, and, finally, modeling and forecasting
these financial time series using data mining methods.
Our main purpose is to provide much needed guidance for applying new
predictive and decision-enhancing hybrid methods to financial tasks such as
capital-market investments, trading, banking services, and many others.
The very complex and challenging problem of forecasting financial time
series requires specific methods of data mining. We discuss these requirements
and show the relations between problem requirements and the capabilities
of different methods. Relational data mining as a hybrid learning
method combines the strength of inductive logic programming (ILP) and
probabilistic inference to meet this challenge. A special feature of the book
is the large number of worked examples illustrating the theoretical concepts
discussed.
The book begins with problem definitions, modern methodologies of
general data mining and financial knowledge discovery, relations between
data mining and database management, current practice, and intellectual
challenges in data mining.
Chapter 2 is devoted to numerical data mining learning models and their
financial applications. We consider ARIMA models, Markov chains, instance-
based learning, neural networks, methods of learning from experts
(“expert” mining”), and new methods for testing the results of data mining.
Chapter 3 presents rule-based and hybrid data mining methods such as
learning prepositional rules (decision trees and DNF), extracting rules from
learned neural networks, learning probabilistic rules, and knowledge-based
stochastic modeling (Markov chains and hidden Markov models) in
finance.
Chapter 4 describes a new area of data mining and financial applications -
- relational data mining (RDM) methods. From our viewpoint, this approach
will play a key role in future advances in data mining methodology and
practice. Topics covered in this chapter include the relational data mining
paradigm and current challenges, theory, and algorithms (FOIL, FOCL and
MMDR).
Numerical relational data mining methods are especially important for
financial analysis where data commonly are numerical financial time series.
This subject is developed in chapters 4, 5 and 6 using complex data types
and representative measurement theory. The RDM paradigm is based on
highly expressive first-order logic language and inductive logic programming.
Chapters 5 and 6 cover knowledge representation and financial applications
of RDM. Chapter 6 also discusses key performance issues of the selected
methods in forecasting financial time series. Chapter 7 presents fuzzy
logic methods combined with probabilistic methods, comparison of fuzzy
logic and probabilistic methods, and their financial applications.
Well-known and commonly used data mining methods in finance are attribute-
based learning methods such as neural networks, the nearest neighbours
method, and decision trees. These are relatively simple, efficient, and
can handle noisy data. However, these methods have two serious drawbacks:
a limited ability to represent background knowledge and the lack of complex
relations. The purpose of relational data mining is to overcome these limitations.
On the other hand, as Bratko and Muggleton noted [1995], current
relational methods (ILP methods) are relatively inefficient and have rather
limited facilities for handling numerical data. Biology, pharmacology, and
medicine have already benefited significantly from relational data mining.
We believe that now is the time for applying these methods to financial
analyses. This book is addressed to researchers, consultants, and students
interested in the application of mathematics to investment, economics, and
management. We also maintain a related website
http://www.cwu.edu/~borisk/finanace.

TABLE OF CONTENTS
Foreword by Gregory Piatetsky-Shapiro xi
Preface xiii
Acknowledgements xv
1. The Scope and Methods of the Study 1
2. Numerical Data Mining Models with Financial Applications 21
3. Rule-Based and Hybrid Financial Data Mining 71
4. Relational Data Mining (RDM) 115
5. Financial Applications of Relational Data Mining 189
6 Comparison of Performance of RDM and other methods in financial applications 219
7. Fuzzy logic approach and its financial applications 231
REFERENCES 285
Subject Index 299

Web Data Mining And Applications In Business Intelligence and Counter-Terrorism

2008-04-22 19:41:33

Preface
BACKGROUND
Recent developments in information systems technologies have resulted in computerizing many applications in various business areas. Data has become a critical resource in many organizations, and therefore, accessing data efficiently, sharing the data, extracting information from the data, and making use of the information have become urgent needs. As a result, not only have there been many efforts toward integrating the various data sources scattered across several sites, but extracting information from these databases in the form of patterns and trends has also become important. These data sources may be databases managed by database management systems or they could be data warehoused in a repository from multiple data sources. The advent of the World Wide Web (WWW) in the mid-1990s has resulted in even greater demand for managing data, information, and knowledge effectively. There is now so much data on the Web that managing it with conventional tools is becoming almost an impossibility. New tools and techniques are needed to effectively manage this data. Therefore, to provide interoperability as well as warehousing between the multiple data sources and systems, and to extract information from the databases and warehouses on the Web, various tools are being developed.

We have written a series of books for CRC Press on data management:

Book #1 (Data Management Systems Evolution and Interoperation) focused on general aspects of data management and also addressed interoperability and migration.

Book #2 (Data Mining: Technologies, Techniques, Tools, and Trends) discussed data mining. Essentially, it elaborated on Chapter 9 of Book #1.

Book #3 (Web Data Management and E-Commerce) discussed Web database technologies and discussed E-commerce as an application area. Essentially, it elaborated on Chapter 10 of Book #1.

Book #4 (Managing and Mining Multimedia Databases) addressed both multimedia database management and multimedia data mining. It elaborated on both Chapter 6 of Book #1 (for multimedia database management) and Chapter 11 of Book #2 (for multimedia data mining).

Book #5 (XML, Databases, and the Semantic Web) described XML technologies related to data management. It expanded on Chapter 11 of Book #3.

This book (Book #6) elaborates on Chapter 12 of Book #5. It describes Web data mining technologies and discusses some critical applications in business intelligence and counter-terrorism. In particular, we discuss techniques and technologies for mining data on the Web, and then describe applications for Web mining, such as customer relationship management, and the increasingly important area of counter-terrorism.

Table of Contents
Web Data Mining and Applications in Business Intelligence and Counter-Terrorism
Preface
Chapter 1 - Introduction
Part I - Supporting Technologies for Web Data Mining
Chapter 2 - The World Wide Web, E-Commerce, and Business Intelligence
Chapter 3 - Data Mining
Chapter 4 - Core Data Mining Technologies
Chapter 5 - Web Database Management
Chapter 6 - Information Retrieval Systems
Chapter 7 - Information Management Technologies
Chapter 8 - The Semantic Web
Part II - Web Data Mining—Techniques, Tools, and Trends
Chapter 9 - Data Mining and the Web
Chapter 10 - Processes and Techniques for Web Data Mining
Chapter 11 - Mining Databases on the Web
Chapter 12 - Information Retrieval and Web Data Mining
Chapter 13 - Information Management and Web Data Mining
Chapter 14 - Semantic Web Mining
Chapter 15 - Mining Usage Patterns and Structure on the Web
Chapter 16 - Prototypes, Products, and Standards for Web Data Mining
Chapter 17 - Some Applications for Web Mining
Part III - Web Data Mining for Counter-Terrorism
Chapter 18 - Some Information on Terrorism, Security Threats, and Protection Measures
Chapter 19 - Web Data Mining for Counter-Terrorism
Chapter 20 - Mining Web Databases for Counter-Terrorism
Chapter 21 - Information Retrieval and Web Mining for Counter-Terrorism
Chapter 22 - Information Management and Web Mining for Counter-Terrorism
Chapter 23 - Semantic Web Mining for Counter-Terrorism
Chapter 24 - Web Usage and Structure Mining for Counter-Terrorism
Chapter 25 - National Security, Privacy, Civil Liberties, and Web Mining
Chapter 26 - Revisiting Security Threats with Respect to Web Mining
Chapter 27 - E-Commerce, Business Intelligence, and Counter-Terrorism
Chapter 28 - Summary and Directions
Part IV - Appendixes
Appendix A - Data Management Systems—Developments and Trends
Appendix B - Database Systems and Related Technologies
Appendix C - Data and Information Security
Appendix D - References
Index
List of Exhibits

Beginning.Database.Design.From.Novice.to.Professional

2008-03-28 15:34:55

this book will definitely be very useful to you if you need to design
a small database. But most importantly, it will help you design a database that can grow,
into terabytes if need be. Design is to databases what grammar is to languages: the foun-
dation. As grammar prevents ambiguities and lets you express your ideas as clearly in a
short note as in a long essay, proper design prevents loss of data integrity and lets you
extract from your databases the information that is hidden in data. Implementation
varies; principles remain the same.

Understanding Digital Libraries

2008-03-26 22:35:43

Editorial Reviews

Review
"Lesk is the senior and most knowledgeable author in the field. His dry humor and clear explanations, combined with his uncanny ability to uncover and address key ideas and problems, make this a "must read."
--Edward A. Fox, Ph.D., Professor of Computer Science, Virginia Tech

"Michael Lesk does for digital libraries what David Macaulay does for every day objects: he lucidly depicts how things work. In the digital world the ways things work is necessarily always in flux. In this second edition, Michael Lesk has done a masterful job of making us feel more at home with this flux."
--Michèle Valerie Cloonan, Dean and Professor, Graduate School of Library & Information Science, Simmons College

"Lesk's insights are distilled from a lifetime of pioneering activities in information retrieval, text processing and digital libraries, culminating in a most creative period at the National Science Foundation. He has written a book that brings these insights alive with well-chosen examples: facts and figures, tables and graphs. Digital libraries have not replaced books. This book illustrates why."
--William Y. Arms, Professor of Computer Science and Co-Director of Information Science, Cornell University

Book Description
This fully revised and updated second edition of Understanding Digital Libraries focuses on the challenges faced by both librarians and computer scientists in a field that has been dramatically altered by the growth of the Web.

At every turn, the goal is practical: to show you how things you might need to do are already being done, or how they can be done. The first part of the book is devoted to technology and examines issues such as varying media requirements, indexing and classification, networks and distribution, and presentation. The second part of the book is concerned with the human contexts in which digital libraries function. Here youll find specific and useful information on usability, preservation, scientific applications, and thorny legal and economic questions.

Useful for digital library projects in all kinds of settings, including commercial and community ventures, museums, research institutions, and schools.
Covers the entire spectrum of media, including text, all kinds of images, audio, and video.
Provides practical advice on achieving the best of what is possible while avoiding common pitfalls.
Filled with case studies and references to valuable outside resources.

Database System Concepts(高清晰版)

2008-03-26 19:19:36

Front Matter 1
Preface 1
1. Introduction 11
Text 11
I. Data Models 35
Introduction 35
2. Entity?Relationship Model 36
3. Relational Model 87
II. Relational Databases 140
Introduction 140
4. SQL 141
5. Other Relational Languages 194
6. Integrity and Security 229
7. Relational?Database Design 260
III. Object?Based Databases and XML 307
Introduction 307
8. Object?Oriented Databases 308
9. Object?Relational Databases 337
10. XML 363
IV. Data Storage and Querying 393
Introduction 393
11. Storage and File Structure 394
12. Indexing and Hashing 446
13. Query Processing 494
14. Query Optimization 529
V. Transaction Management 563
Introduction 563
15. Transactions 564
16. Concurrency Control 590
17. Recovery System 637
iii
VI. Database System Architecture 679
Introduction 679
18. Database System Architecture 680
19. Distributed Databases 705
20. Parallel Databases 750
VII. Other Topics 773
Introduction 773
21. Application Development and Administration 774
22. Advanced Querying and Information Retrieval 810
23. Advanced Data Types and New Applications 856
24. Advanced Transaction Processing 884

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