Intelligent Technologies for Information Analysis (eBook, PDF)

Redaktion: Zhong, Ning; Liu, Jiming

• Format: PDF

Produktbeschreibung

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.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 711
• Erscheinungstermin: 14. März 2013
• Englisch
• ISBN-13: 9783662079522
• Artikelnr.: 53397443

Autorenporträt

  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 Institute of Technology, he was an associate professor in Department of Computer Science and Systems Engineering, Yamaguchi University, Japan. He is also a guest professor of Beijing University of Technology since 1998. He is the co-founder and co-chair of Web Intelligence Consortium (WIC), vice chair of the executive committee of the IEEE Computer Society Technical Committee on Computational Intelligence (TCCI), the advisory board of ACM SIGART, steering committee of IEEE International Conferences on Data Mining (ICDM), the advisory board of International Rough Set Society, steering committee of Pacific-Asia Conferences on Knowledge Discovery and Data Mining (PAKDD), coordinator and member of advisory board of a Special Interest Group on Granular Computing in Berkeley Initiative in Soft Computing (BISC/SIG-GrC). Even more information can be found on his home page http://www.kis-lab.com/zhong/   Dr. Jiming Liu is the Head of Computer Science Department at Hong Kong Baptist University (HKBU). He leads the AAMAS/AOC Research Group (i.e., Autonomous Agents and Multi-Agent Systems / Autonomy-Oriented Computing) at HKBU. He holds a B.Sc. degree in Physics from East China Normal University in Shanghai, an M.A. degree in Educational Technology from Concordia University in Montreal, and an M.Eng. and a Ph.D. degrees both in Electrical Engineering from McGill University in Montreal. In Feb.-July 1999, Dr. Liu was an invited Visiting Scholar in Computer Science Department, Stanford University, where he was associated with the AI & Robotics Laboratory and taught advanced graduate classes on topicsrelated to Robot Learning, Neural Robots, and Evolutionary Robotics. He is Guest Professor at University of Science and Technology of China, East China Normal University (Software Engineering Institute), and Beijing University of Technology, as well as Adjunct Fellow at E-Business Technology Institute (ETI - a joint partnership institute between IBM and University of Hong Kong). Dr. Liu is the co-founder of Web Intelligence Consortium (WIC), an international organization dedicated to promoting world-wide scientific research and industrial development in the era of Web and agent Intelligence. He has founded andserved, or is serving, as Program, Conference, Workshop, and General Chairs for several international conferences and workshops, including The IEEE/WIC International Conference on Web Intelligence (WI) series and The IEEE/WIC International Conference on Intelligent Agent Technology (IAT) series, and is presently serving as the Senior Program Committee Member, Program Committee Member, and Steering/Planning Committee Member for many major international conferences.  

Inhaltsangabe

1. The Alchemy of Intelligent IT (iIT): A Blueprint for Future Information Technology.- I. Emerging Data Mining Technology.- 2. Grid-Based Data Mining and Knowledge Discovery.- 3. The MiningMart Approach to Knowledge Discovery in Databases.- 4. Ensemble Methods and Rule Generation.- 5. Evaluation Scheme for Exception Rule/Group Discovery.- 6. Data Mining for Targeted Marketing.- II. Data Mining for Web Intelligence.- 7. Mining for Information Discovery on the Web: Overview and Illustrative Research.- 8. Mining Web Logs for Actionable Knowledge.- 9. Discovery of Web Robot Sessions Based on Their Navigational Patterns.- 10. Web Ontology Learning and Engineering: An Integrated Approach.- 11. Browsing Semi-Structured Texts on the Web Using Formal Concept Analysis.- 12. Graph Discovery and Visualization from Textual Data.- III. Emerging Agent Technology.- 13. Agent Networks: Topological and Clustering Characterization.- 14. Finding the Best Agents for Cooperation.- 15. Constructing Hybrid Intelligent Systems for Data Mining from Agent Perspectives.- 16. Making Agents Acceptable to People.- IV. Emerging Soft Computing Technology.- 17. Constraint-Based Neural Network Learning for Time Series Predictions.- 18. Approximate Reasoning in Distributed Environments.- 19. Soft Computing Pattern Recognition, Data Mining and Web Intelligence.- 20. Dominance-Based Rough Set Approach to Knowledge Discovery (I): General Perspective.- 21. Dominance-Based Rough Set Approach to Knowledge Discovery (II): Extensions and Applications.- V. Statistical Learning Theory.- 22. Bayesian Ying Yang Learning (I): A Unified Perspective for Statistical Modeling.- 23. Bayesian Ying Yang Learning (II): A New Mechanism for Model Selection and Regularization.- Author Index.