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- W58790516 abstract "This chapter presents a new knowledge-based approach to mitigate problems related to scenario-specific information retrieval (IR). The use of metathesaurus and semantic structure in the UMLS to extract key concepts from the free text for indexing, phrase-based indexing for representing similar concepts, and query expansion to improve the probability of matching query terms with the terms in the document is preferred. A scenario typically refers to a specific health care task, such as searching for treatment methods for a specific disease. Although traditional systems are useful for general information retrieval, these systems cannot support scenario-specific IR because: the terms in the query posed by the user may not use a standardized medical vocabulary; there is no effective technique to represent synonyms, phrases, and similar concepts in free text; and the terms used in a query and those used in a document for representing the same topic may be mismatched. A new knowledge-based approach for retrieving scenario-specific free-text documents has been developed, which consists of three integrated components: IndexFinder, phrase-based VSM, and knowledge-based query expansion. IndexFinder extracts key terms from free text, generating conceptual terms by permuting words in a sentence rather than using the traditional techniques based on NLP. The phrase-based VSM has been developed for document retrieval. Knowledge-based query expansion techniques and the phrase-based VSM can be used in conjunction to significantly improve precision and recall." @default.
- W58790516 created "2016-06-24" @default.
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- W58790516 date "2008-01-01" @default.
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- W58790516 title "KMeX" @default.
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- W58790516 doi "https://doi.org/10.1016/b978-012373583-6.50018-9" @default.
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