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By Myunggwon Hwang, Hyunjang Kong, Sunkyoung Baek, Pankoo Kim (auth.), Stéphane Marchand-Maillet, Eric Bruno, Andreas Nürnberger, Marcin Detyniecki (eds.)

ISBN-10: 3540715444

ISBN-13: 9783540715443

ISBN-10: 3540715452

ISBN-13: 9783540715450

This e-book constitutes the completely refereed post-proceedings of the 4th foreign Workshop on Adaptive Multimedia Retrieval, AMR 2006, held in Geneva, Switzerland in July 2006. The 18 revised complete papers awarded including 2 invited papers have been conscientiously chosen in the course of rounds of reviewing and development. additionally integrated are invited contributions which have been meant to open on less-addressed issues locally, because it is the case for tune details retrieval and dispensed details retrieval. The papers are equipped in topical sections on ontology-based retrieval and annotation, score and similarity measurements, tune info retrieval, visible modelling, adaptive retrieval, structuring multimedia, in addition to person integration and profiling.

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Additional info for Adaptive Multimedia Retrieval: User, Context, and Feedback: 4th International Workshop, AMR 2006, Geneva, Switzerland, July 27-28, 2006, Revised Selected Papers

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Magdeburg, 2005. 27. I. Schmitt and N. Schulz. Similarity Relational Calculus and its Reduction to a Similarity Algebra. In Proc. of 3rd Intern. Symposium on Foundations of Information and Knowledge Systems (FoIKS’04), pages 252–272. Springer-Verlag, 2004. 28. I. Schmitt, N. Schulz, and T. Herstel. WS-QBE: A QBE-like Query Language for Complex Multimedia Queries. In Proc. of the 11th Int. Multimedia Modelling Conf. (MMM’05), pages 222–229. IEEE CS Press, 2005. 29. N. Schulz and I. Schmitt. A Survey of Weighted Scoring Rules in Multimedia Database Systems.

Section 3 discusses the ontology concept that we used in this study. The design and architecture of our model are introduced in Section 4. An example domain used as a case study in this paper is described in Section 5, before we draw the conclusions in Section 6. 2 Modeling Components A video data model is different from a traditional data model and should include the elements that represent the video content. It should also be able to capture and represent various types of information about video objects along with their structures, operations and properties, as well as relationships among objects.

G. the algebraic sum, distributivity cannot be guaranteed. Furthermore, we are faced with problems of failing associativity and distributivity [29] when Fagin’s weighting schema is used, even on the min/max pair. Table 1 summarizes the properties of the approaches discussed so far. The problem of dominance turns out to be even more serious when we examine the way how fuzzy logic is utilized for query evaluation. As shown in Fig. 5 (left) 22 C. Hentschel et al. Table 1. Properties of different approaches to combine retrieval and database queries approach boolean query retrieval query fuzzy logic (min/max) fuzzy logic (not min/max) weighted fuzzy logic scores no yes yes yes yes distributivity yes — yes no no non-dominating — — no yes — fuzzy logic relies on importing scores (here two score functions) and truth values (here from one database condition) and interpreting them as membership values.

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Adaptive Multimedia Retrieval: User, Context, and Feedback: 4th International Workshop, AMR 2006, Geneva, Switzerland, July 27-28, 2006, Revised Selected Papers by Myunggwon Hwang, Hyunjang Kong, Sunkyoung Baek, Pankoo Kim (auth.), Stéphane Marchand-Maillet, Eric Bruno, Andreas Nürnberger, Marcin Detyniecki (eds.)


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