Advances in Web Intelligence and Data Mining
1st Edition
Published on 11. August 2006
XVI, 340 pages
978-3-540-33880-2 (ISBN)
Description
Today, in the middle of the ?rst decade of the 21st century, the Internet has become a major communication medium, where virtually any kind of content can be transferred instantly and reliably between individual users and entire - ganizations located in any part of the globe. The World Wide Web (WWW) has a tremendous e?ect on our daily activities at work and at home. Consequently, more e?ective and e?cient methods and technologies are needed to make the most of the Web's nearly unlimited potential. The new Web-related research directions include intelligent methods usually associated with the ?elds of c- putational intelligence, soft computing, and data mining. AWIC, the "Atlantic Web Intelligence Conferences" continue to be a forum for exchange of new ideas and novel practical solutions in this new and exciting area. The conference was born as an initiative of the WIC-Poland and the WIC- Spain Research Centers, both belonging to the Web Intelligence Consortium - WIC (http://wi-consortium.org/). Prior to this year, three AWIC conferences have been held: in Madrid, Spain (2003), in Cancun, Mexico (2004), and in L´ od´ z, Poland (2005). AWIC 2006 took place in Beer-Sheva, Israel during June 5-7, 2006, organized locally by Ben-Gurion University of the Negev. The book presents state-of-the-art developments in the ?eld of computati- ally intelligent methods applied to various aspects and ways of Web exploration.
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Mark Last | Piotr S. Szczepaniak | Zeev Volkovich
Advances in Web Intelligence and Data Mining
Book
05/2006
Springer
€160.49
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Content
1.- DataRover: An Automated System for Extracting Product Information From Online Catalogs.- A New Path Generalization Algorithm for HTML Wrapper Induction.- Trustworthiness Measurement Methodology for e-Business.- Routing Using Messengers in Sparse and Disconnected Mobile Sensor Networks.- Content Consistency Model for Pervasive Internet Access.- Content Description Model and Framework for Efficient Content Distribution.- Exploiting Wikipedia in Integrating Semantic Annotation with Information Retrieval.- Ontology based Query Rewriting on Integrated XML based Information Systems.- Visually Exploring Concept-Based Fuzzy Clusters in Web Search Results.- A Grid Scheduling Optimization Strategy Based on Fuzzy Multi-Attribute Group Decision-Making.- An Adaptive PC to Mobile Web Contents Transcoding System Based on MPEG-21 Multimedia Framework.- Recommendation Framework for Online Social Networks.- Packet Manipulating Based on Zipf's Distribution to Protect from Attack in P2P Information Retrieval.- Investigation of the Fuzzy System for the Assessment of Cadastre Operators' Work.- DLAIP: A Description Logic Based Approach for Dynamic Semantic Web Services Composition.- Adding Support to User Interaction in Egovernment Environment.- Using Consensus Methodology in Processing Inconsistency of Knowledge.- Creating Synthetic Temporal Document Collections for Web Archive Benchmarking.- Predicting Stock Trends with Time Series Data Mining and Web Content Mining.- CatS: A Classification-Powered Meta-Search Engine.- A Decision Tree Framework for Semi-Automatic Extraction of Product Attributes from the Web.- A Dynamic Generation Algorithm for Meta Process in Intelligent Platform of Virtual Travel Agency.- Linguistic Summaries of Standardized Documents.- A Web-knowledge-basedClustering Model for Gene Expression Data Analysis.- 2.- Estimations of Similarity in Formal Concept Analysis of Data with Graded Attributes.- Kernels for the Relevance Vector Machine - An Empirical Study.- A Decision-Tree Framework for Instance-space Decomposition.- On prokaryotes' clustering based on curvature distribution.- Look-Ahead Mechanism Integration in Decision Tree Induction Models.- Feature Selection by Combining Multiple Methods.- Clustering and Classification of Textual Documents Based on Fuzzy Quantitative Similarity Measure - a Practical Evaluation.- Oriented k-windows: A PCA driven clustering method.- A cluster stability criteria based on the two-sample test concept.
