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Information-theoretic semantic multimedia indexing

Magalhães, João and Rüger, Stefan (2007). Information-theoretic semantic multimedia indexing. In: ACM International Conference on Image and Video Retrieval (CIVR), 9-11 Jul 2007, Amsterdam, The Netherlands.

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To solve the problem of indexing collections with diverse text documents, image documents, or documents with both text and images, one needs to develop a model that supports heterogeneous types of documents. In this paper, we show how information theory supplies us with the tools necessary to develop a unique model for text, image, and text/image retrieval. In our approach, for each possible query keyword we estimate a maximum entropy model based on exclusively continuous features that were pre-processed. The unique continuous feature-space of text and visual data is constructed by using a minimum description length criterion to find the optimal feature-space representation (optimal from an information theory point of view). We evaluate our approach in three experiments: only text retrieval, only image retrieval, and text combined with image retrieval.

Item Type: Conference or Workshop Item
Copyright Holders: 2007 ACM
Extra Information: Best paper award

Proceedings of the 6th ACM International Conference on Image and Video Retrieval, CIVR 2007,
Amsterdam, The Netherlands, July 9-11, 2007
Nicu Sebe, Marcel Worring (Eds.)
ISBN 978-1-59593-733-9
Keywords: multimedia indexing; minimum description length; multi-modal categorization; information retrieval
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 29588
Depositing User: Stefan Rüger
Date Deposited: 28 Sep 2011 12:59
Last Modified: 10 Dec 2018 23:24
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