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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.
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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.
Titel: Knowledge Discovery Enhanced with Semantic ...
Verlag: Springer
Erscheinungsdatum: 2009
Einband: Hardcover
Zustand: New
Anbieter: Buchpark, Trebbin, Deutschland
Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar. Bestandsnummer des Verkäufers 5406869/12
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Anbieter: Brook Bookstore On Demand, Napoli, NA, Italien
Zustand: new. Questo è un articolo print on demand. Bestandsnummer des Verkäufers 807c7ca90bcc96fb6a123c9e93831736
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Anbieter: moluna, Greven, Deutschland
Gebunden. Zustand: 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. Bestandsnummer des Verkäufers 5043521
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Buch. Zustand: 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. Bestandsnummer des Verkäufers 9783642018909
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: 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. Bestandsnummer des Verkäufers 9783642018909
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