Knowledge discovery enhanced with semantic and social information
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 Discover...
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| Weitere Verfasser: | , , , , , , , |
| Format: | Livre numérique |
| Sprache: | Anglais |
| Veröffentlicht: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Ausgabe: | 1st ed. 2009. |
| Schriftenreihe: | Studies in Computational Intelligence
220 |
| Online Zugang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Knowledge discovery enhanced with semantic and social information, Bettina Berendt, Dunja Mladenič, Marco de gemmis... [et al.], eds., Berlin, Springer, 2009, 1 vol. (X-143 p.), Studies in computational intelligence, 978-3-642-01890-9 |
| Zusammenfassung: | 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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| Beschreibung: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ISBN: | 9783642018916 |
| ISSN: | 1860-9503 |
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