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.
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Fedor Bakalov received PhD in Computer Science from Friedrich Schiller University of Jena. During his doctoral research, he investigated the transparency and usability issues of adaptive systems. Fedor is author of over 25 peer-reviewed publications and was twice granted IBM PhD Fellowship award. He also holds Master and Bachelor of Engineering.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 244 pp. Englisch. Seller Inventory # 9783659357077
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bakalov FedorFedor Bakalov received PhD in Computer Science from Friedrich Schiller University of Jena. During his doctoral research, he investigated the transparency and usability issues of adaptive systems. Fedor is author of over . Seller Inventory # 5150801
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Taschenbuch. Condition: Neu. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 244 pp. Englisch. Seller Inventory # 9783659357077
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9783659357077
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