Automatic personalization based on Web usage mining
Communications of the ACM
User Modeling and User-Adapted Interaction
Hypermedia Presentation Adaptation on the Semantic Web
AH '02 Proceedings of the Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
A Framework for the Evaluation of Session Reconstruction Heuristics in Web-Usage Analysis
INFORMS Journal on Computing
Rules for an Ontology-based Approach to Adaptation
SMAP '06 Proceedings of the First International Workshop on Semantic Media Adaptation and Personalization
Web Semantics: Science, Services and Agents on the World Wide Web
WISE'07 Proceedings of the 8th international conference on Web information systems engineering
RW'07 Proceedings of the Third international summer school conference on Reasoning Web
Editorial: Application integration on the user interface level: An ontology-based approach
Data & Knowledge Engineering
Efficient semantic event processing: lessons learned in user interface integration
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part II
Dynamic customization of a remote conversation support system: agent-based approach
KES-AMSTA'12 Proceedings of the 6th KES international conference on Agent and Multi-Agent Systems: technologies and applications
Agent-based customization of a remote conversation support system
Intelligent Decision Technologies
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The need for adaptive and personalized Rich Internet Application puts a new dimension to already existing approaches of Adaptive Hypermedia Systems. Instead of computing the adaptation steps at the server, Rich Internet Applications need a client-side approach that can react immediately on user input. In this paper we present a novel approach that holistically combines page annotations, semantic Web usage mining, user modeling, ontologies and rules to adapt AJAX pages. The focus of our pater is the conceptual introduction of the autonomous client. An autonomous client directly executes all necessary adaptation steps based on a user model, without requesting any logic on the server. In order to realize this, we use ontologies to annotate Rich Internet Applications and to describe the user model as well as semantic Web usage mining for detecting adaptation rules. Additionally, we provide a detailed overview and evaluation of how we moved resource-intensive ontology processing and rules execution from the server to the client.