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Narrowing the semantic gap - improved text-based web document retrieval using visual features
IEEE transactions on multimedia
In this paper, we present the results of our work that seek to negotiate the gap between low-level features and high-level concepts in the domain of web document retrieval. This work concerns a technique, latent semantic indexing (LSI), which has been used for textual information retrieval for many years. In this environment, LSI determines clusters of co-occurring keywordssometimes called concepts-so that a query which uses a particular keyword can then retrieve documents perhaps notdoi:10.1109/tmm.2002.1017733 fatcat:52qgrls22fho7ogfoct3vt7zye