Adaptive Multimedia Retrieval. Identifying, Summarizing, and by Matthias Geier, Sascha Spors, Stefan Weinzierl (auth.), PDF

By Matthias Geier, Sascha Spors, Stefan Weinzierl (auth.), Marcin Detyniecki, Ulrich Leiner, Andreas Nürnberger (eds.)

ISBN-10: 3642147585

ISBN-13: 9783642147586

This quantity constitutes the refereed lawsuits of the sixth overseas Workshop on Adaptive Multimedia Retrieval, AMR 2008, held in Berlin, Germany, in June 2008.

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Additional info for Adaptive Multimedia Retrieval. Identifying, Summarizing, and Recommending Image and Music: 6th International Workshop, AMR 2008, Berlin, Germany, June 26-27, 2008. Revised Selected Papers

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If the evaluation discovers a conflict, it has to be traced to show to the user the contradictory ordering relations, so the user can decide the next step. g. by deselecting conflicting ordering relations. The other is to let the algorithm choose to skip conflicting parts of the poset to ensure at least a maximized possible solution with less constraints. Conflicting parts can be discovered by a brute force approach testing all subsets of the provided poset against the results of the optimization of the given query.

Wiley, New York (2002) 19. : Designing the user interface: Strategies for effective human– computer interaction, 4th edn. Pearson, Boston (2005) A Poset Based Approach for Condition Weighting 39 20. : Imprecision and User Preferences in Multimedia Queries: A Generic Algebraic Approach. , Thalheim, B. ) FoIKS 2000. LNCS, vol. 1762, pp. 50–71. Springer, Heidelberg (2000) 21. : Similarity Relational Calculus and its Reduction to a Similarity Algebra. a. ) FoIKS 2004. LNCS, vol. 2942, pp. 252–272. Springer, Heidelberg (2004) 22.

2. Profiles with Rk as the rank in the list, if the observed song is within the top n ranks, otherwise Ak = 0. Large values for Ak indicate high similarity to the query song. The entire set of profiles, extracted with regard to a query song Qj , is combined to a profile set Πj . In Fig. 2, two profiles are presented computed with n = 250. The samples are rated differently, one positive (a), the other negative (b). The negative rated song is within the top ten ranks in the playlist. With regard to the structure of the according profile it is apparent that the song occurs in each of the considered lists, which leads to a large aggregation score.

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Adaptive Multimedia Retrieval. Identifying, Summarizing, and Recommending Image and Music: 6th International Workshop, AMR 2008, Berlin, Germany, June 26-27, 2008. Revised Selected Papers by Matthias Geier, Sascha Spors, Stefan Weinzierl (auth.), Marcin Detyniecki, Ulrich Leiner, Andreas Nürnberger (eds.)


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