• DocumentCode
    2124806
  • Title

    A Concept-Relation Vector Model Based Method for Web Document Retrieval

  • Author

    Liu, Yuan ; Zhanhuai, Li ; Longbo, Zhang ; Shiliang, Chen

  • Author_Institution
    Sch. of Comput. Sci., Northwestern Poly Tech. Univ., Xian
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    196
  • Lastpage
    200
  • Abstract
    Semantic information has been paid much attention in web IR. Although many researches have improved the retrieval performance by employing WordNet synset and concept, relations between concepts are often ignored by most of the semantic retrieval methods. We propose a relation enhanced concept vector model CRVM(concept-relation vector model) for document representation in this paper, and the documents to be retrieved are indexed by both concepts and relations. Domain ontology is employed to provide background knowledge for constructing concept based vector representation of documents. We prove the effectiveness of ontology concept and relation enhanced document representation for retrieving by web pages derived from WebKB data set and Open Directory Project.
  • Keywords
    Internet; Web sites; document handling; information retrieval; ontologies (artificial intelligence); Open Directory Project; Web document retrieval; Web pages; WebKB data set; WordNet synset; concept-relation vector model based method; document representation; domain ontology; semantic retrieval methods; Computational efficiency; Computer science; Frequency; Information analysis; Information retrieval; Knowledge acquisition; Navigation; Ontologies; Semantic Web; Web pages; information retrieval; ontology; semantic retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3488-6
  • Type

    conf

  • DOI
    10.1109/KAM.2008.130
  • Filename
    4732814