• DocumentCode
    3310590
  • Title

    English-persian text retrieval using concept graph

  • Author

    Teymoorian, Farnaz ; Mohsenzadeh, Mehran ; Seyyedi, MirAli

  • Author_Institution
    Dept. of Comput. Eng., Islamic Azad Univ. - North Tehran Branch, Tehran, Iran
  • fYear
    2009
  • fDate
    8-11 Aug. 2009
  • Firstpage
    447
  • Lastpage
    451
  • Abstract
    Cross-language information retrieval (CLIR) is the retrieval process where the user presents queries in one language to retrieve documents in another language. In this field the resolution of lexical ambiguity in translating queries is a key challenge. In this paper, we propose a technique for calculating translation probabilities based on creating query terms´ concept graphs for selecting the right translation sense of query terms for English-Persian text retrieval. We present an efficient statistical method for creating this graph. We test the effectiveness of the proposed disambiguation method on Hamshahri collection1 that is standardized according to CLEF standards. Evaluation using this data collection shows great effectiveness of the proposed method.
  • Keywords
    graph theory; language translation; natural languages; probability; query processing; statistical analysis; text analysis; English-Persian text retrieval; concept graph; cross-language information retrieval; disambiguation method; lexical ambiguity; query translation; statistical method; translation probability; Concrete; Costs; Cryptography; Polynomials; Security; Concept graph; Term Weighting; Text retrieval; Translation disambiguation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-4519-6
  • Electronic_ISBN
    978-1-4244-4520-2
  • Type

    conf

  • DOI
    10.1109/ICCSIT.2009.5234499
  • Filename
    5234499