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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 weredoi:10.1145/1282280.1282368 dblp:conf/civr/MagalhaesR07 fatcat:buqjdgf4dfdf5l76i7xyivjwou