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- rvk_ss%3a%2200 74500 allgemeines %2f buch- und bibliothekswesen%2c informationswissenschaft %2f bibliothekswesen %2f kataloge%2c katalogisierung %2f titelaufnahme%2c katalogisierungs im ausland %28.6 1%29 %2f international%2c allgemeinen%22 2
- rvk_ss%3a%2200 74500 allgemeines %2f buch- und bibliothekswesen%2c informationswissenschaft %2f bibliothekswesen %2f kataloge%2c katalogisierung %2f titelaufnahme%2c katalogisierungs im auslands %28.6 1%29 %2f international%2c allgemeines%22 2
- rvk_ss%3a%2200 74500 allgemeines %2f buch- und bibliothekswesen%2c informationswissenschaft %2f bibliothekswesen %2f kataloge%2c katalogisierung %2f titelaufnahmen%2c katalogisierungs im ausland %28.6 1%29 %2f international%2c allgemeines%22 2
- rvk_ss%3a%2200 74500 allgemeines %2f buch- und bibliothekswesen%2c informationswissenschaft %2f bibliothekswesen %2f kataloge%2c katalogisierungs %2f titelaufnahme%2c katalogisierungs im ausland %28.6 1%29 %2f international%2c allgemeines%22 2
- rvk_ss%3a%2200 74500 allgemeines %2f buch- und bibliothekswesen%2c informationswissenschaft %2f bibliothekswesen %2f katalogen%2c katalogisierung %2f titelaufnahme%2c katalogisierungs im ausland %28.6 1%29 %2f international%2c allgemeines%22 2
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Rindflesch, T.C.; Aronson, A.R.: Semantic processing in information retrieval (1993)
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- Date
- 29. 6.2015 14:51:28
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Wright, L.W.; Nardini, H.K.G.; Aronson, A.R.; Rindflesch, T.C.: Hierarchical concept indexing of full-text documents in the Unified Medical Language System Information sources Map (1999)
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- Abstract
- Full-text documents are a vital and rapidly growing part of online biomedical information. A single large document can contain as much information as a small database, but normally lacks the tight structure and consistent indexing of a database. Retrieval systems will often miss highly relevant parts of a document if the document as a whole appears irrelevant. Access to full-text information is further complicated by the need to search separately many disparate information resources. This research explores how these problems can be addressed by the combined use of 2 techniques: 1) natural language processing for automatic concept-based indexing of full text, and 2) methods for exploiting the structure and hierarchy of full-text documents. We describe methods for applying these techniques to a large collection of full-text documents drawn from the Health Services / Technology Assessment Text (HSTAT) database at the NLM and examine how this hierarchical concept indexing can assist both document- and source-level retrieval in the context of NLM's Information Source Map project