Intelligent Technologies for Information Analysis

✍ Scribed by Prof. Ning Zhong, Prof. Jiming Liu (auth.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2004
• Tongue: English
• Leaves: 723
• Edition: 1
• Category: Library

✦ Synopsis

Intelligent Information Technology (iiT) encompasses the theories and ap­ plications of artificial intelligence, statistical pattern recognition, learning theory, data warehousing, data mining and knowledge discovery, Grid com­ puting, and autonomous agents and multi-agent systems in the context of today's as well as future IT, such as Electronic Commerce (EC), Business Intelligence (BI), Social Intelligence (SI), Web Intelligence (WI), Knowledge Grid (KG), and Knowledge Community (KC), among others. The multi-author monograph presents the current state of the research and development in intelligent technologies for information analysis, in par­ ticular, advances in agents, data mining, and learning theory, from both the­ oretical and application aspects. It investigates the future of information technology (IT) from a new intelligent IT (iiT) perspective, and highlights major iiT-related topics by structuring an introductory chapter and 22 sur­ vey/research chapters into 5 parts: (1) emerging data mining technology, (2) data mining for Web intelligence, (3) emerging agent technology, ( 4) emerging soft computing technology, and (5) statistical learning theory. Each chapter includes the original work of the author(s) as well as a comprehensive survey related to the chapter's topic. This book will become a valuable source of reference for R&D profession­ als active in advanced intelligent information technologies. Students as well as IT professionals and ambitious practitioners concerned with advanced in­ telligent information technologies will appreciate the book as a useful text enhanced by numerous illustrations and examples.

✦ Table of Contents

Front Matter....Pages I-XXVII
The Alchemy of Intelligent IT (iIT): A Blueprint for Future Information Technology....Pages 1-16
Front Matter....Pages 17-17
Grid-Based Data Mining and Knowledge Discovery....Pages 19-45
The MiningMart Approach to Knowledge Discovery in Databases....Pages 47-65
Ensemble Methods and Rule Generation....Pages 67-87
Evaluation Scheme for Exception Rule/Group Discovery....Pages 89-108
Data Mining for Targeted Marketing....Pages 109-131
Front Matter....Pages 133-133
Mining for Information Discovery on the Web: Overview and Illustrative Research....Pages 135-168
Mining Web Logs for Actionable Knowledge....Pages 169-191
Discovery of Web Robot Sessions Based on Their Navigational Patterns....Pages 193-222
Web Ontology Learning and Engineering: An Integrated Approach....Pages 223-242
Browsing Semi-Structured Texts on the Web Using Formal Concept Analysis....Pages 243-264
Graph Discovery and Visualization from Textual Data....Pages 265-288
Front Matter....Pages 289-289
Agent Networks: Topological and Clustering Characterization....Pages 291-310
Finding the Best Agents for Cooperation....Pages 311-332
Constructing Hybrid Intelligent Systems for Data Mining from Agent Perspectives....Pages 333-359
Making Agents Acceptable to People....Pages 361-406
Front Matter....Pages 407-407
Constraint-Based Neural Network Learning for Time Series Predictions....Pages 409-431
Approximate Reasoning in Distributed Environments....Pages 433-474
Soft Computing Pattern Recognition, Data Mining and Web Intelligence....Pages 475-512
Dominance-Based Rough Set Approach to Knowledge Discovery (I): General Perspective....Pages 513-552
Front Matter....Pages 407-407
Dominance-Based Rough Set Approach to Knowledge Discovery (II): Extensions and Applications....Pages 553-612
Front Matter....Pages 613-613
Bayesian Ying Yang Learning (I): A Unified Perspective for Statistical Modeling....Pages 615-659
Bayesian Ying Yang Learning (II): A New Mechanism for Model Selection and Regularization....Pages 661-706
Back Matter....Pages 707-711

✦ Subjects

Information Storage and Retrieval; Probability and Statistics in Computer Science; Math Applications in Computer Science; Information Systems Applications (incl. Internet); Artificial Intelligence (incl. Robotics); Probability Theory and