Document retrieval from a citation database using conceptual clustering and co-word analysis.

Traditional document retrieval techniques are ineffective in finding relevant documents due to a lack of semantic understanding of relevance. In this article, two techniques are described - conceptual clustering and co-word analysis - aimed at injecting intelligence into the retrieval of documents s...

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Publicado en:Online Information Review Vol. 28; no. 1; pp. 22 - 33
Autores principales: Hui SC, Fong ACM
Formato: equations & formulas pictorial tables/charts Journal Article
Publicado: Emerald Publishing Limited 2004
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Document retrieval from a citation database using conceptual clustering and co-word analysis.
      aug:
        au:
          Hui SC
          Fong ACM
        affil: Associate Professor, School of Computer Engineering, Nanyang Technological University, Singapore
      sug:
        subj:
          Database Management Software
          Full-Text Databases
          Information Retrieval
          Abstracting and Indexing
          Knowbots
          Natural Language Processing
          Semantics
          Subject Headings
      ab: Traditional document retrieval techniques are ineffective in finding relevant documents due to a lack of semantic understanding of relevance. In this article, two techniques are described - conceptual clustering and co-word analysis - aimed at injecting intelligence into the retrieval of documents stored in a citation database. Performance analysis has revealed that these techniques are better than traditional lexical analysis in terms of retrieval speed and accuracy.
      pubtype: Academic Journal
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        equations & formulas
        pictorial
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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