Intelligent Technologies for Information Analysis by Ning ZhongIntelligent Technologies for Information Analysis by Ning Zhong

Intelligent Technologies for Information Analysis

byNing ZhongEditorJiming Liu

Paperback | November 30, 2010

Pricing and Purchase Info

$225.96 online 
$260.95 list price save 13%
Earn 1,130 plum® points

Prices and offers may vary in store


In stock online

Ships free on orders over $25

Not available in stores


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.
 Ning Zhong is currently head of Knowledge Information Systems Laboratory, and a professor in Department of Systems and Information Engineering, Graduate School, Maebashi Institute of Technology, Japan. He is also CEO of Web Intelligence Laboratory, Inc., a new type of venture intelligent IT business company. Before moving to Maebashi ...
Title:Intelligent Technologies for Information AnalysisFormat:PaperbackDimensions:711 pages, 23.5 × 15.5 × 0.07 inPublished:November 30, 2010Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3642073786

ISBN - 13:9783642073786


Table of Contents

1) The Alchemy of Intelligent IT (iIT) (Ning Zhong, Jiming Liu) Part I Emerging Data Mining Technology ======================================= 2) Grid-Based Data Mining and Knowledge Discovery (Mario Cannataro, Antonio Congiusta, Carlo Mastroianni, Andrea Pugliese, Domenico Talia, Paolo Trunfio) 3) The MiningMart Approach to Knowledge Discovery in Databases (Katharina Morik, Martin Scholz) 4) Ensemble Methods and Rule Generation (Yongdai Kim, Jinseog Kim, Jongwoo Jeon) 5) Evaluation Scheme for Exception Rule/Group Discovery (Einoshin Suzuki) 6) Data Mining for Direct Marketing (Ning Zhong, Yiyu Yao, Chunnian Liu, Chuangxin Ou, Jiajin Huang) Part II Data Mining for Web Intelligence ========================================= 7) Mining for Information Discovery on the Web (Hwanjo Yu, An Hai Doan, Jiawei Han) 8) Mining Web Logs for Actionable Knowledge (Qiang Yang, Charles X. Ling, Jianfeng Gao) 9) Discovery of Web Robot Sessions Based on Their Navigational Patterns (Pang-Ning Tan, Vipin Kumar) 10) Web Ontology Learning and Engineering (Roberto Navigli, Paola Velardi, Michele Missikoff) 11) Browsing Semi-Structured Texts on the Web Using Formal Concept Analysis (Richard Cole, Peter Eklund, Florence Amardeilh) 12) Graph Discovery and Visualization from Textual Data (Vincent Dubois, Mohamed Quafafou) Part III Emerging Agent Technology =================================== 13) Agent Networks: Topological and Clustering Characterization (Xiaolong Jin, Jiming Liu) 14) Finding the Best Agents for Cooperation (Francesco Buccafurri, Domenico Rosaci, Giuseppe L.M. Sarne, Luigi Palopoli) 15) Constructing Hybrid Intelligent Systems for Data Mining from Agent Perspectives (Zili Zhang, Zhengqi Zhang) 16) Making Agents Acceptable to People (Jeffrey M. Bradshaw, Patrick Beautement, Maggie R. Breedy, Larry Bunch, Sergey V. Drakunov, Paul J. Feltovich, Robert R. Hoffman, Renia Jeffers, Matthew Johnson, Shriniwas Kulkarnt, James Lott, Anil K. Raj, Niranjan Suri, Andrzej Uszok) Part IV Emerging Soft Computing Technology =========================================== 17) Constraint-Based Neural Network Learning for Time Series Predictions (Benjamin W. Wah, Minglun Qian) 18) Approximate Reasoning in Distributed Environments (Andrzej Skowron) 19) Soft Computing Pattern Recognition, Data Mining, and Web Intelligence (Sankar K. Pal, Sushmita Mitra, Pabitra Mitra) 20) Dominance-Based Rough Set Approach to Knowledge Discovery (I) (Salvatore Greco, Benedetto Matarazzo, Roman Slowinski) 21) Dominance-Based Rough Set Approach to Knowledge Discovery (II) (Salvatore Greco, Benedetto Matarazzo, Roman Slowinski) Part V Statistical Learning Theory =================================== 22) Mining Dependence Structures (I) -- A General Statistical Learning Perspective -- (Lei Xu) 23) Mining Dependence Strucutres (II) -- An Independence Analysis Perspective -- (Lei Xu)