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Titlebook: Emergent Web Intelligence: Advanced Semantic Technologies; Youakim Badr,Richard Chbeir,Aboul-Ella Hassanien Book 2010 Springer-Verlag Lond

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發(fā)表于 2025-3-21 19:11:09 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Emergent Web Intelligence: Advanced Semantic Technologies
編輯Youakim Badr,Richard Chbeir,Aboul-Ella Hassanien
視頻videohttp://file.papertrans.cn/309/308186/308186.mp4
概述Covers introductory material suitable for undergraduate and post-graduate students, advanced material suitable for research students, researchers, practitioners and university lecturers.Basic concepts
叢書名稱Advanced Information and Knowledge Processing
圖書封面Titlebook: Emergent Web Intelligence: Advanced Semantic Technologies;  Youakim Badr,Richard Chbeir,Aboul-Ella Hassanien Book 2010 Springer-Verlag Lond
描述The success of the World Wide Web depends on the ability of users to store, p- cess and retrieve digital information regardless of distance boundaries, languages and domains of knowledge. The universality and ?exibility of the World Wide Web have also enabled the rapid growth of a variety of new services and applications based on human–machine interaction. The semantics of exchanged information and services should be useful not only for human to human communications, but also in that machines would be able to understand and automatically process web content. Semanticsgive well-de?nedmeaningto web content and enable computersand p- ple to work in cooperation. Today, the crucial challenge becomes the development of languages to express information in a machine processable format. Now more than ever, new advanced techniques and intelligent approaches are required to tra- form the Web into a universal reasoning and computing machine. Web intelligence attempts to deal with this challenge by exploiting information technologies and - ti?cial intelligence approaches to design the next generation of web-empowered systems and services.
出版日期Book 2010
關鍵詞Collaboration; artificial intelligence; classification; fuzzy; groupware; information system; intelligence
版次1
doihttps://doi.org/10.1007/978-1-84996-077-9
isbn_softcover978-1-4471-2561-7
isbn_ebook978-1-84996-077-9Series ISSN 1610-3947 Series E-ISSN 2197-8441
issn_series 1610-3947
copyrightSpringer-Verlag London 2010
The information of publication is updating

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Semantic Web Technologies and Artificial Neural Networks for Intelligent Web Knowledge Source DiscovN) models that can be used for intelligent web knowledge source discovery in the new and emergent Semantic Web..The purpose of the Semantic Web is to introduce semantic content in the huge amount of unstructured or semi-structured information sources available on the web by using ontologies. An onto
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Mining of Semantic Image Content Using Collective Web Intelligenceve intelligence, visual judgment and mental evaluation. For high-level semantic image features and concepts, such processes of intelligent judgment cannot be mechanized or carried out automatically by machines. In this chapter, an indexing method is described whereby the aggregate intelligence of di
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Suited Support for Distributed Web Intelligence Cooperative Workrmed in the field of the “Semantic Web”. These efforts are based on technological components such as the XML, RDF, and OWL languages that allow the cooperative definition of distributed ontologies. From these components, it is possible to develop “reasoning” programs that are able a) to infer inform
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Toward Distributed Knowledge Discovery on?Grid Systemsand management of useful information of this data is becoming a challenge and a massive economic need. This led to the development of distributed data mining techniques to deal with huge multi-dimensional datasets distributed among several sites..Besides, to cope with large, graphically distributed,
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An Analysis of Constructed Categories for?Textual Classification Using Fuzzy Similarity and Agglomerhis work proposes a text categorizer using the methodology of Fuzzy Similarity. The clustering algorithms Stars and Cliques are adopted in the Agglomerative Hierarchical method and they identify the groups of texts by specifying some type of relationship rule to create categories based on the simila
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