By Stephan Baumann, Rafael Schirru, Bernhard Streit (auth.), Marcin Detyniecki, Peter Knees, Andreas Nürnberger, Markus Schedl, Sebastian Stober (eds.)
This ebook constitutes the refereed court cases of the eighth overseas convention on Adaptive Multimedia Retrieval, AMR 2010, held in Linz, Austria, in August 2010. The 14 revised complete papers and the invited contribution provided have been rigorously reviewed and chosen from a number of submissions. The papers are geared up in topical sections on Context-based personalization; media info fusion; video retrieval; audio and song retrieval; adaptive similarities; and discovering and organizing.
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Additional resources for Adaptive Multimedia Retrieval. Context, Exploration, and Fusion: 8th International Workshop, AMR 2010, Linz, Austria, August 17-18, 2010, Revised Selected Papers
The General User Model Ontology is based on OWL and is used for modeling user attributes and their interrelationships. The authors selected the user’s attributes that are modeled in user-adaptive systems as well as user’s interests and preferences. The construction of the user model ontology GUMO was based on the thought to divide the description of user model attributes into three elements: auxiliary predicate - range. This description is called a situational statement. For example, the interests of a user in music could be described in the following way: auxiliary=hasInterest, predicate=music, and range=low-medium-high.
Each UUCM attribute is represented by the following features: attribute name, attribute qualiﬁer, attribute value, value qualiﬁer, value probability, and attribute dimension. Moreover, the four UUCM dimensions selected for the context model are the Cognitive Pattern, the Task, the Relationship, and 22 A. Nika et al. the Environment. Finally, relevant subsets of the user context model are deﬁned that are called user’s working contexts and are used to distinguish the diﬀerent roles that the user can play.
Mediation of User Models for Enhanced Personalization in Recommender Systems. J. User Modeling and User Adapted Interaction 18(3), 245–286 (2008) 4. : Presentation of a modular framework for interpretation of sensor data with dynamic Bayesian networks on mobile devices. In: LWA 2004, Lernen Wissensentdeckung Adaptivit¨ at, Berlin, Germany, pp. 9–10 (2004) 5. : Geo Referenced Dynamic Bayesian Networks for User Positioning on Mobile Systems. , Linnhoﬀ-Popien, C. ) LoCA 2005. LNCS, vol. 3479, pp.
Adaptive Multimedia Retrieval. Context, Exploration, and Fusion: 8th International Workshop, AMR 2010, Linz, Austria, August 17-18, 2010, Revised Selected Papers by Stephan Baumann, Rafael Schirru, Bernhard Streit (auth.), Marcin Detyniecki, Peter Knees, Andreas Nürnberger, Markus Schedl, Sebastian Stober (eds.)