Scrutable Adaptivity in Community-Enabled Web Portals - Bakalov, Fedor
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This book presents a framework for scrutable adaptivity in community-enabled web portals. The framework provides four models that an adaptive system needs for personalization: (1) a user model representing information about individual users, (2) a metadata repository providing annotations of content, (3) domain model defining machine-processable semantics of the domain knowledge used for modeling user features and annotating content, and (4) personalization rules defining the logic of adaptation. Also, the framework provides methods for keeping these models up-to-date, complete, and accurate.…mehr

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Produktbeschreibung
This book presents a framework for scrutable adaptivity in community-enabled web portals. The framework provides four models that an adaptive system needs for personalization: (1) a user model representing information about individual users, (2) a metadata repository providing annotations of content, (3) domain model defining machine-processable semantics of the domain knowledge used for modeling user features and annotating content, and (4) personalization rules defining the logic of adaptation. Also, the framework provides methods for keeping these models up-to-date, complete, and accurate. Among others, these methods leverage the technology for Natural Language Processing and the willingness of the user community to contribute and annotate content. Furthermore, the framework provides graphical user interfaces and interaction patters for allowing users to view and adapt these models.
Autorenporträt
Fedor Bakalov received his M.Eng. in Information Management from Asian Institute of Technology in Thailand in 2007. He is currently working towards his Ph.D. at the University of Jena, Germany. His research interests include Adaptive Hypermedia, User Modeling, HCI, and Semantic Web.