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...ion. Often, users won’t express their preferences directly, but the application might infer preferences from a user profile or other context information, and amend an explicit query accordingly (e.g. =-=[24]-=-). Various techniques for preference mining and elicitation have already been developed, e.g. [25, 26], which can be used in Semantic Web applications as well. 7 Conclusion In this paper we showed tha...

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...blication Reader. A. Architectural Overview of the Personal Reader Framework The Personal Reader Framework 1 is an environment for designing, implementing and maintaining personal Web-content Readers =-=[41]-=-, [56]. These personal Webcontent Readers allow a user to browse information (the Reader part), and to access personal recommendations and contextual information on the currently regarded Web resource...

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...hes and how our system differs. In AHAM [11], like in many other systems, the adaptation model relies on condition-action rules. Theses rules provide adaptation as well as user model update. Condition-action rules can trigger each other, and thus often need to GLAM: A Generic Layered Adaptation Model 139 be restricted to ensure termination and confluence. On the contrary, in our rule system, the nature of rules prevents us from termination problems, and we implemented a verification algorithm which can check if the system is deterministic in all cases, i.e. confluent. The adaptation system in [13] uses TRIPLE rules for directly interrogating the user and domain data. These rules can recommend documents, which is close from action selection. Moreover, the recommendations can be more or less strong, which is close to our notion of possibility/desirability/preference. However, the layering in our system allows to separate different semantic levels in our data: preferences and knowledge are dealt with separately in GLAM, in order to simplify the conception of the system. By using distinct rule levels, we prevent an AHS creator from writing very long rules, with many premises. This layering...

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...be performed [12]. In a review conducted by Karampiperis et al (2005), the authors identified the current state of the art adaptive hypermedia systems as AHA! [13], OntoAIMS [14], the Personal Reader =-=[15]-=-, WINDS [16], ACCT [17]. These systems are based on the AHAM. This model builds upon the Dexter model, that is, a common model for hypertext-based systems that was designed for general purpose adaptiv...

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...so several cognitive styles and how they relate to learning. Baldoni [10] describes how SCORM contents can be adapted using metadata, and how it can be used with the semantic web. The Personal Reader =-=[11]-=- is also another important work in the eLearning field, it also uses the semantic web to personalize and enrich eLearning contents. In the same research line, Dolog [12] argues that the semantic web c...

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...e contain semantic annotation (created manually or discovered automatically by software tools). Personalized navigation is realized using meta-data description and employing Semantic Web technologies =-=[11]-=-. The aim of this paper is to present a method for personalized navigation support based on afore mentioned approaches. The method is intended for large information spaces with frequent changes of inf...

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...’s browsing behaviour to decide the user’s knowledge, background and interests. However, AHA! does not support social features such as tagging, rating, feedback as in MOT 2.0. The personal reader in (=-=Dolog et al. 2004-=-) uses semantic web technologies to enrich and personalize the learning resources. This work is very interesting, but is still in progress. Our approach does not rely heavily on semantic web technique...