• DocumentCode
    2927744
  • Title

    Text Information Retrieval Based on Concept Semantic Similarity

  • Author

    Lv, Gang ; Zheng, Cheng ; Zhang, Li

  • Author_Institution
    Key Lab. of Network & Intell. Inf. Process., Hefei Univ., Hefei, China
  • fYear
    2009
  • fDate
    12-14 Oct. 2009
  • Firstpage
    356
  • Lastpage
    360
  • Abstract
    In this paper, an improved method of calculating ontology semantic similarity is proposed to enhance the information retrieval recall and precision. To filter out the document which have smaller related degree with original query, the scores of search results document is re-calculated by use of ontology semantic similarity. A new definition of the iterative query expansion parameters is put forward which can reduce the number of expansion and further improve the efficiency of the query. The use of open source tools for text semantic retrieval test, i.e., Jena and Lucene, has verified the feasibility and effectiveness of the proposed method.
  • Keywords
    information retrieval; iterative methods; ontologies (artificial intelligence); query processing; calculating ontology semantic; concept semantic similarity; further improve efficiency; iterative query expansion; search results document; text information retrieval; Computer networks; Context modeling; Grid computing; Information processing; Information retrieval; Intelligent networks; Laboratories; Ontologies; Signal processing; Solid modeling; Document Scores; Information Retrieval; Ontology; Query Expansion; Semantic Similarity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantics, Knowledge and Grid, 2009. SKG 2009. Fifth International Conference on
  • Conference_Location
    Zhuhai
  • Print_ISBN
    978-0-7695-3810-5
  • Type

    conf

  • DOI
    10.1109/SKG.2009.18
  • Filename
    5370020