This is the authors' abstract. We don't add key points for this paper.
Traditional approaches to information retrieval are based upon representing a user's query as a bag of query terms and a document as a bag of index terms and computing a degree of similarity between the two based on the overlap or number of query terms in common between them. Our long-term approach to IR applications is based upon precomputing semantically-based word-word similarities, work which is described elsewhere, and using these as part of the document-query similarity measure. A basic premise of our word-to-word similarity measure is that the input to this computation is the correct or intended word sense but in information retrieval applications, automatic and accurate word sense disambiguation remains an unsolved problem. In this paper we describe our first successful application of these ideas to an information retrieval application, specifically the indexing and retrieval of captions describing the content of images. We have hand-captioned 2714 images and to circumvent, fo...
Answers are grounded in this paper and cite their sources.
No takes yet. Share an insight, caveat, or question.
Smeaton et al. (1996) studied this question.
Synapse has enriched 8 closely related papers on similar clinical questions. Consider them for comparative context: