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.
"synopsis" may belong to another edition of this title.
This book is a showcase of recent advances in knowledge discovery enhanced with semantic and social information. It includes eight contributed chapters that grew out of two joint workshops at ECML/PKDD 2007.
There is general agreement that the effectiveness of Machine Learning and Knowledge Discovery output strongly depends not only on the quality of source data and the sophistication of learning algorithms, but also on additional input provided by domain experts. There is less agreement on whether, when and how such input can and should be formalized as explicit prior knowledge.
The six chapters in the first part of the book aim to investigate this aspect by addressing four different topics: inductive logic programming; the role of human users; investigations of fully automated methods for integrating background knowledge; the use of background knowledge for Web mining. The two chapters in the second part are motivated by the Web 2.0 (r)evolution and the increasingly strong role of user-generated content. The contributions emphasize the vision of the Web as a social medium for content and knowledge sharing.
"About this title" may belong to another edition of this title.
£ 7.51 shipping from Germany to United Kingdom
Destination, rates & speedsFREE shipping from U.S.A. to United Kingdom
Destination, rates & speedsSeller: Basi6 International, Irving, TX, U.S.A.
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Seller Inventory # ABEJUNE24-325752
Quantity: 1 available
Seller: Buchpark, Trebbin, Germany
Condition: Sehr gut. Zustand: Sehr gut | Seiten: 146 | Sprache: Englisch | Produktart: Bücher. Seller Inventory # 5406869/12
Quantity: 1 available
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In. Seller Inventory # ria9783642018909_new
Quantity: Over 20 available
Seller: moluna, Greven, Germany
Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents latest results on knowledge discovery enhanced with semantic and social informationPrior Conceptual Knowledge in Machine Learning and Knowledge Discovery.- On Ontologies as Prior Conceptual Knowledge in Inductive Logic Programming.- A Kn. Seller Inventory # 5043521
Quantity: Over 20 available
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is a showcase of recent advances in knowledge discovery enhanced with semantic and social information. It includes eight contributed chapters that grew out of two joint workshops at ECML/PKDD 2007.There is general agreement that the effectiveness of Machine Learning and Knowledge Discovery output strongly depends not only on the quality of source data and the sophistication of learning algorithms, but also on additional input provided by domain experts. There is less agreement on whether, when and how such input can and should be formalized as explicit prior knowledge.The six chapters in the first part of the book aim to investigate this aspect by addressing four different topics: inductive logic programming; the role of human users; investigations of fully automated methods for integrating background knowledge; the use of background knowledge for Web mining. The two chapters in the second part are motivated by the Web 2.0 (r)evolution and the increasingly strong role of user-generated content. The contributions emphasize the vision of the Web as a social medium for content and knowledge sharing. 143 pp. Englisch. Seller Inventory # 9783642018909
Quantity: 2 available
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a showcase of recent advances in knowledge discovery enhanced with semantic and social information. It includes eight contributed chapters that grew out of two joint workshops at ECML/PKDD 2007.There is general agreement that the effectiveness of Machine Learning and Knowledge Discovery output strongly depends not only on the quality of source data and the sophistication of learning algorithms, but also on additional input provided by domain experts. There is less agreement on whether, when and how such input can and should be formalized as explicit prior knowledge.The six chapters in the first part of the book aim to investigate this aspect by addressing four different topics: inductive logic programming; the role of human users; investigations of fully automated methods for integrating background knowledge; the use of background knowledge for Web mining. The two chapters in the second part are motivated by the Web 2.0 (r)evolution and the increasingly strong role of user-generated content. The contributions emphasize the vision of the Web as a social medium for content and knowledge sharing. Seller Inventory # 9783642018909
Quantity: 2 available
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. pp. 156 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam. Seller Inventory # 6508334
Quantity: 1 available
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. 156. Seller Inventory # 261372401
Quantity: 1 available
Seller: California Books, Miami, FL, U.S.A.
Condition: New. Seller Inventory # I-9783642018909
Quantity: Over 20 available
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. pp. 156. Seller Inventory # 181372411
Quantity: 1 available