[PDF] Computational Web Intelligence Intelligent Technology For Web Applications eBook

Author : Yan-Qing Zhang
Publisher : World Scientific
Page : 584 pages
File Size : 50,50 MB
Release : 2004
Category : Computers
ISBN : 9812388273

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- The book completely introduces the intelligent Web techniques based on soft computing, granular computing, computational intelligence, and Web technology for different intelligent Web applications - The first book to introduce the novel intelligent Web theory (computational Web intelligence) with many potential intelligent Web applications - The book introduces CWI techniques for currently hot and important applications such as Web security, Internet security, bioinformatics, Web search engines, Web mining, e-commerce, intelligent Web agents, etc.

Author : Yan-qing Zhang
Publisher : World Scientific
Page : 584 pages
File Size : 23,94 MB
Release : 2004-08-25
Category : Computers
ISBN : 9814482811

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This review volume introduces the novel intelligent Web theory called computational Web intelligence (CWI) based on computational intelligence (CI) and Web technology (WT). It takes an in-depth look at hybrid Web intelligence (HWI), which is based on artificial biological and computational intelligence with Web technology and is used to build hybrid intelligent Web systems that serve wired and wireless users more efficiently. The basic principles of CWI and various e-applications of CWI and HWI are discussed. For completeness, six major CWI techniques — fuzzy Web intelligence, neural Web intelligence, evolutionary Web intelligence, granular Web intelligence, rough Web Intelligence and probabilistic Web intelligence — are described. With the huge potential for intelligent e-business applications of CWI and HWI, these techniques represent the future of intelligent Web applications.

Author : Ajith Abraham
Publisher : Springer
Page : 397 pages
File Size : 33,67 MB
Release : 2009-05-01
Category : Technology & Engineering
ISBN : 3642010911

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Foundations of Computational Intelligence Volume 6: Data Mining: Theoretical Foundations and Applications Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, business, health care, banking, retail, and many others. Advanced representation schemes and computational intelligence techniques such as rough sets, neural networks; decision trees; fuzzy logic; evolutionary algorithms; arti- cial immune systems; swarm intelligence; reinforcement learning, association rule mining, Web intelligence paradigms etc. have proved valuable when they are - plied to Data Mining problems. Computational tools or solutions based on intel- gent systems are being used with great success in Data Mining applications. It is also observed that strong scientific advances have been made when issues from different research areas are integrated. This Volume comprises of 15 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Int- ligence techniques for Data Mining. The book is divided into 3 parts: Part-I: Data Click Streams and Temporal Data Mining Part-II: Text and Rule Mining Part-III: Applications Part I on Data Click Streams and Temporal Data Mining contains four chapters that describe several approaches in Data Click Streams and Temporal Data Mining.

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 2390 pages
File Size : 19,77 MB
Release : 2018-06-04
Category : Computers
ISBN : 1522556443

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Ongoing advancements in modern technology have led to significant developments in intelligent systems. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Intelligent Systems: Concepts, Methodologies, Tools, and Applications contains a compendium of the latest academic material on the latest breakthroughs and recent progress in intelligent systems. Including innovative studies on information retrieval, artificial intelligence, and software engineering, this multi-volume book is an ideal source for researchers, professionals, academics, upper-level students, and practitioners interested in emerging perspectives in the field of intelligent systems.

Author : Zeeshan-Ul-Hassan Usmani
Publisher : BoD – Books on Demand
Page : 496 pages
File Size : 15,66 MB
Release : 2010-03-01
Category : Computers
ISBN : 9537619850

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This book presents a unique and diversified collection of research work ranging from controlling the activities in virtual world to optimization of productivity in games, from collaborative recommendations to populate an open computational environment with autonomous hypothetical reasoning, and from dynamic health portal to measuring information quality, correctness, and readability from the web.

Author : Xiaotie Deng
Publisher : Springer Science & Business Media
Page : 1209 pages
File Size : 24,98 MB
Release : 2005-12-09
Category : Computers
ISBN : 3540309357

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This book constitutes the refereed proceedings of the 16th International Symposium on Algorithms and Computation, ISAAC 2005, held in Sanya, Hainan, China in December 2005. The 112 revised full papers presented were carefully reviewed and selected from 549 submissions. The papers are organized in topical sections on computational geometry, computational optimization, graph drawing and graph algorithms, computational complexity, approximation algorithms, internet algorithms, quantum computing and cryptography, data structure, computational biology, experimental algorithm mehodologies and online algorithms, randomized algorithms, parallel and distributed algorithms.

Author : Ioannis Vlahavas
Publisher : IGI Global
Page : 384 pages
File Size : 40,10 MB
Release : 2005-01-01
Category : Business & Economics
ISBN : 9781591404514

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The Intelligent Techniques for Planning presents a number of modern approaches to the area of automated planning. These approaches combine methods from classical planning such as the construction of graphs and the use of domain-independent heuristics with techniques from other areas of artificial intelligence. This book discuses, in detail, a number of state-of-the-art planning systems that utilize constraint satisfaction techniques in order to deal with time and resources, machine learning in order to utilize experience drawn from past runs, methods from knowledge systems for more expressive representation of knowledge and ideas from other areas such as Intelligent Agents. Apart from the thorough analysis and implementation details, each chapter of the book also provides extensive background information about its subject and presents and comments on similar approaches done in the past.

Author : Robert P W Duin
Publisher : World Scientific
Page : 634 pages
File Size : 44,42 MB
Release : 2005-11-22
Category : Computers
ISBN : 9814479144

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This book provides a fundamentally new approach to pattern recognition in which objects are characterized by relations to other objects instead of by using features or models. This 'dissimilarity representation' bridges the gap between the traditionally opposing approaches of statistical and structural pattern recognition.Physical phenomena, objects and events in the world are related in various and often complex ways. Such relations are usually modeled in the form of graphs or diagrams. While this is useful for communication between experts, such representation is difficult to combine and integrate by machine learning procedures. However, if the relations are captured by sets of dissimilarities, general data analysis procedures may be applied for analysis.With their detailed description of an unprecedented approach absent from traditional textbooks, the authors have crafted an essential book for every researcher and systems designer studying or developing pattern recognition systems.

Author : K. G. Subramanian
Publisher : World Scientific
Page : 422 pages
File Size : 34,62 MB
Release : 2006
Category : Language Arts & Disciplines
ISBN : 9812568891

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A collection of articles by leading experts in theoretical computer science, this volume commemorates the 75th birthday of Professor Rani Siromoney, one of the pioneers in the field in India. The articles span the vast range of areas that Professor Siromoney has worked in or influenced, including grammar systems, picture languages and new models of computation.

Author : Adam Schenker
Publisher : World Scientific
Page : 250 pages
File Size : 24,92 MB
Release : 2005
Category : Computers
ISBN : 9812563393

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This book describes exciting new opportunities for utilizing robust graph representations of data with common machine learning algorithms. Graphs can model additional information which is often not present in commonly used data representations, such as vectors. Through the use of graph distance ? a relatively new approach for determining graph similarity ? the authors show how well-known algorithms, such as k-means clustering and k-nearest neighbors classification, can be easily extended to work with graphs instead of vectors. This allows for the utilization of additional information found in graph representations, while at the same time employing well-known, proven algorithms.To demonstrate and investigate these novel techniques, the authors have selected the domain of web content mining, which involves the clustering and classification of web documents based on their textual substance. Several methods of representing web document content by graphs are introduced; an interesting feature of these representations is that they allow for a polynomial time distance computation, something which is typically an NP-complete problem when using graphs. Experimental results are reported for both clustering and classification in three web document collections using a variety of graph representations, distance measures, and algorithm parameters.In addition, this book describes several other related topics, many of which provide excellent starting points for researchers and students interested in exploring this new area of machine learning further. These topics include creating graph-based multiple classifier ensembles through random node selection and visualization of graph-based data using multidimensional scaling.