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Computational Web Intelligence Intelligent Technology For Web Applications
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Book Synopsis Computational Web Intelligence by : Yan-Qing Zhang
Download or read book Computational Web Intelligence written by Yan-Qing Zhang and published by World Scientific. This book was released on 2004 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: - 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.
Book Synopsis Computational Web Intelligence: Intelligent Technology For Web Applications by : Yan-qing Zhang
Download or read book Computational Web Intelligence: Intelligent Technology For Web Applications written by Yan-qing Zhang and published by World Scientific. This book was released on 2004-08-25 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 :Management Association, Information Resources Publisher :IGI Global ISBN 13 :1522556443 Total Pages :2351 pages Book Rating :4.5/5 (225 download)
Book Synopsis Intelligent Systems: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources
Download or read book Intelligent Systems: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2018-06-04 with total page 2351 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Foundations of Computational Intelligence by : Ajith Abraham
Download or read book Foundations of Computational Intelligence written by Ajith Abraham and published by Springer. This book was released on 2009-05-01 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Web Intelligence and Intelligent Agents by : Zeeshan-Ul-Hassan Usmani
Download or read book Web Intelligence and Intelligent Agents written by Zeeshan-Ul-Hassan Usmani and published by BoD – Books on Demand. This book was released on 2010-03-01 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Algorithms and Computation by : Xiaotie Deng
Download or read book Algorithms and Computation written by Xiaotie Deng and published by Springer Science & Business Media. This book was released on 2005-12-09 with total page 1209 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Intelligent Techniques for Planning by : Ioannis Vlahavas
Download or read book Intelligent Techniques for Planning written by Ioannis Vlahavas and published by IGI Global. This book was released on 2005-01-01 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Dissimilarity Representation For Pattern Recognition, The: Foundations And Applications by : Robert P W Duin
Download or read book Dissimilarity Representation For Pattern Recognition, The: Foundations And Applications written by Robert P W Duin and published by World Scientific. This book was released on 2005-11-22 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Mining With Decision Trees: Theory And Applications by : Lior Rokach
Download or read book Data Mining With Decision Trees: Theory And Applications written by Lior Rokach and published by World Scientific. This book was released on 2007-12-17 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first comprehensive book dedicated entirely to the field of decision trees in data mining and covers all aspects of this important technique.Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining, the science and technology of exploring large and complex bodies of data in order to discover useful patterns. The area is of great importance because it enables modeling and knowledge extraction from the abundance of data available. Both theoreticians and practitioners are continually seeking techniques to make the process more efficient, cost-effective and accurate. Decision trees, originally implemented in decision theory and statistics, are highly effective tools in other areas such as data mining, text mining, information extraction, machine learning, and pattern recognition. This book invites readers to explore the many benefits in data mining that decision trees offer:
Book Synopsis Formal Models, Languages and Applications by : K. G. Subramanian
Download or read book Formal Models, Languages and Applications written by K. G. Subramanian and published by World Scientific. This book was released on 2006 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Graph-theoretic Techniques for Web Content Mining by : Adam Schenker
Download or read book Graph-theoretic Techniques for Web Content Mining written by Adam Schenker and published by World Scientific. This book was released on 2005 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Interval Neutrosophic Sets and Logic: Theory and Applications in Computing by : Haibin Wang
Download or read book Interval Neutrosophic Sets and Logic: Theory and Applications in Computing written by Haibin Wang and published by Infinite Study. This book was released on 2005 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the advancements and applications of neutrosophics, which are generalizations of fuzzy logic, fuzzy set, and imprecise probability. The neutrosophic logic, neutrosophic set, neutrosophic probability, and neutrosophic statistics are increasingly used in engineering applications (especially for software and information fusion), medicine, military, cybernetics, physics.In the last chapter a soft semantic Web Services agent framework is proposed to facilitate the registration and discovery of high quality semantic Web Services agent. The intelligent inference engine module of soft semantic Web Services agent is implemented using interval neutrosophic logic.
Book Synopsis Fuzzy Neural Network Theory and Application by : Puyin Liu
Download or read book Fuzzy Neural Network Theory and Application written by Puyin Liu and published by World Scientific. This book was released on 2004 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to help the reader grasp the underlying theory. This is a valuable reference for scientists and engineers working in mathematics, computer science, control or other fields related to information processing. It can also be used as a textbook for graduate courses in applied mathematics, computer science, automatic control and electrical engineering. Contents: Fuzzy Neural Networks for Storing and Classifying; Fuzzy Associative Memory OCo Feedback Networks; Regular Fuzzy Neural Networks; Polygonal Fuzzy Neural Networks; Approximation Analysis of Fuzzy Systems; Stochastic Fuzzy Systems and Approximations; Application of FNN to Image Restoration. Readership: Scientists, engineers and graduate students in applied mathematics, computer science, automatic control and information processing."
Book Synopsis Data Mining with Decision Trees by : Lior Rokach
Download or read book Data Mining with Decision Trees written by Lior Rokach and published by World Scientific. This book was released on 2008 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first comprehensive book dedicated entirely to the field of decision trees in data mining and covers all aspects of this important technique.Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining, the science and technology of exploring large and complex bodies of data in order to discover useful patterns. The area is of great importance because it enables modeling and knowledge extraction from the abundance of data available. Both theoreticians and practitioners are continually seeking techniques to make the process more efficient, cost-effective and accurate. Decision trees, originally implemented in decision theory and statistics, are highly effective tools in other areas such as data mining, text mining, information extraction, machine learning, and pattern recognition. This book invites readers to explore the many benefits in data mining that decision trees offer: Self-explanatory and easy to follow when compacted Able to handle a variety of input data: nominal, numeric and textual Able to process datasets that may have errors or missing values High predictive performance for a relatively small computational effort Available in many data mining packages over a variety of platforms Useful for various tasks, such as classification, regression, clustering and feature selection
Book Synopsis Personalization Techniques and Recommender Systems by : Matthew Y. Ma
Download or read book Personalization Techniques and Recommender Systems written by Matthew Y. Ma and published by World Scientific. This book was released on 2008 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The phenomenal growth of the Internet has resulted in huge amounts of online information, a situation that is overwhelming to the end users. To overcome this problem, personalization technologies have been extensively employed. The book is the first of its kind, representing research efforts in the diversity of personalization and recommendation techniques. These include user modeling, content, collaborative, hybrid and knowledge-based recommender systems. It presents theoretic research in the context of various applications from mobile information access, marketing and sales and web services, to library and personalized TV recommendation systems. This volume will serve as a basis to researchers who wish to learn more in the field of recommender systems, and also to those intending to deploy advanced personalization techniques in their systems. Sample Chapter(s). Personalization-Privacy Tradeoffs in Adaptive Information Access (865 KB). Contents: User Modeling and Profiling: Personalization-Privacy Tradeoffs in Adaptive Information Access (B Smyth); A Deep Evaluation of Two Cognitive User Models for Personalized Search (F Gasparetti & A Micarelli); Unobtrusive User Modeling for Adaptive Hypermedia (H J Holz et al.); User Modelling Sharing for Adaptive e-Learning and Intelligent Help (K Kabassi et al.); Collaborative Filtering: Experimental Analysis of Multiattribute Utility Collaborative Filtering on a Synthetic Data Set (N Manouselis & C Costopoulou); Efficient Collaborative Filtering in Content-Addressable Spaces (S Berkovsky et al.); Identifying and Analyzing User Model Information from Collaborative Filtering Datasets (J Griffith et al.); Content-Based Systems, Hybrid Systems and Machine Learning Methods: Personalization Strategies and Semantic Reasoning: Working in Tandem in Advanced Recommender Systems (Y Blanco-Fernindez et al.); Content Classification and Recommendation Techniques for Viewing Electronic Programming Guide on a Portable Device (J Zhu et al.); User Acceptance of Knowledge-Based Recommenders (A Felfernig et al.); Using Restricted Random Walks for Library Recommendations and Knowledge Space Exploration (M Franke & A Geyer-Schulz); An Experimental Study of Feature Selection Methods for Text Classification (G Uchyigit & K Clark). Readership: Researchers and graduate students in machine learning and databases/information science.
Book Synopsis Artificial General Intelligence by : Patrick Hammer
Download or read book Artificial General Intelligence written by Patrick Hammer and published by Springer Nature. This book was released on 2023-05-23 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th International Conference on Artificial General Intelligence, AGI 2023, held in Stockholm, Sweden in June 2023. The 35 full papers and one short paper presented in this book were carefully reviewed and selected from 72 submissions. The papers cover topics from foundations of AGI, to AGI approaches and AGI ethics, to the roles of systems biology, goal generation, and learning systems, and so much more.
Book Synopsis Bridging the Gap Between Graph Edit Distance and Kernel Machines by : Michel Neuhaus
Download or read book Bridging the Gap Between Graph Edit Distance and Kernel Machines written by Michel Neuhaus and published by World Scientific. This book was released on 2007 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: In graph-based structural pattern recognition, the idea is to transform patterns into graphs and perform the analysis and recognition of patterns in the graph domain ? commonly referred to as graph matching. A large number of methods for graph matching have been proposed. Graph edit distance, for instance, defines the dissimilarity of two graphs by the amount of distortion that is needed to transform one graph into the other and is considered one of the most flexible methods for error-tolerant graph matching.This book focuses on graph kernel functions that are highly tolerant towards structural errors. The basic idea is to incorporate concepts from graph edit distance into kernel functions, thus combining the flexibility of edit distance-based graph matching with the power of kernel machines for pattern recognition. The authors introduce a collection of novel graph kernels related to edit distance, including diffusion kernels, convolution kernels, and random walk kernels. From an experimental evaluation of a semi-artificial line drawing data set and four real-world data sets consisting of pictures, microscopic images, fingerprints, and molecules, the authors demonstrate that some of the kernel functions in conjunction with support vector machines significantly outperform traditional edit distance-based nearest-neighbor classifiers, both in terms of classification accuracy and running time.