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Overview"There is generalagreementthat the quality of Machine Learning and Kno- edgeDiscoveryoutputstronglydependsnotonlyonthequalityofsourcedata andsophisticationoflearningalgorithms,butalsoonadditional,task/domain speci?c input provided by domain experts for the particular session. There is however less agreement on whether, when and how such input can and should e?ectively be formalized and reused as explicit prior knowledge. In the ?rst ofthe two parts into which the book is divided, we aimed to - vestigate current developments and new insights on learning techniques that exploit prior knowledge and on promising application areas. With respect to application areas, experiments on bio-informatics / medical and Web data environments are described. This part comprises a selection of extended c- tributionstothe workshopPrior Conceptual Knowledge inMachine Learning and Knowledge Discovery (PriCKL), held at ECML/PKDD 2007 18th - ropean Conference on Machine Learning and 11th European Conference on PrinciplesandPracticeofKnowledgeDiscoveryinDatabases).Theworkshop is part of the activities of the ""SEVENPRO - Semantic Virtual Engineering for Product Design"" project of the European 6th Framework Programme. The second part of the book has been motivated by the speci?cation of Web 2.0. We observe Web 2.0 as a powerful means of promoting the Web as a social medium, stimulating interpersonal communication and fostering the sharing of content, information, semantics and knowledge among people. Chapters are authored by participants to the workshop Web Mining 2.0, heldatECML/PKDD2007.Theworkshophostedresearchontheroleofweb mininginandfortheWeb2.0.Itispartoftheactivitiesoftheworkinggroups ""UbiquitousData-InteractionandDataCollection""and""HumanComputer Interaction and Cognitive Modelling"" of the Coordination Action ""KDubiq - Knowledge Discovery in Ubiquitous Environments"" of the European 6th Framework Programme." Full Product DetailsAuthor: Bettina Berendt , Dunja Mladenic , Marco de Gemmis , Giovanni SemeraroPublisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K Edition: 2009 ed. Volume: 220 Dimensions: Width: 15.50cm , Height: 1.10cm , Length: 23.50cm Weight: 0.880kg ISBN: 9783642018909ISBN 10: 3642018904 Pages: 143 Publication Date: 29 June 2009 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsPrior Conceptual Knowledge in Machine Learning and Knowledge Discovery.- On Ontologies as Prior Conceptual Knowledge in Inductive Logic Programming.- A Knowledge-Intensive Approach for Semi-automatic Causal Subgroup Discovery.- A Study of the SEMINTEC Approach to Frequent Pattern Mining.- Partitional Conceptual Clustering of Web Resources Annotated with Ontology Languages.- The Ex Project: Web Information Extraction Using Extraction Ontologies.- Dealing with Background Knowledge in the SEWEBAR Project.- Web Mining 2.0.- Item Weighting Techniques for Collaborative Filtering.- Using Term-Matching Algorithms for the Annotation of Geo-services.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |