• DocumentCode
    694819
  • Title

    Research on XML Keyword Query Method Based on Semantic

  • Author

    Guofeng Zhao ; Shan Tian

  • Author_Institution
    Future Internet Res. Center, Chongqing Univ. of Posts & Telecommun., Chongqing, China
  • fYear
    2013
  • fDate
    7-8 Dec. 2013
  • Firstpage
    806
  • Lastpage
    811
  • Abstract
    In this paper, we study the problem of effective keyword search over XML documents, Keyword search for smallest lowest common ancestor(SLCA) in XML data has recently been proposed as a meaningful way to identify interesting data nodes in XML data where their sub trees contain an input set of keywords. XML retrieval technology has been concerned widely by information retrieval researchers. XML data contains rich semantic information, but most of query methods can´t make full use of the semantic information. There will be missed case if there is no enough semantic information. This paper proposed a new XML keyword query algorithm based on semantic(SKSA) to solve the question above. The algorithm takes full use of the node semantic information based on structural semantic. The same or similar results will be returned to users if there is no the keyword in XML document, which avoids the missed case. The test experiment result on the real XML data sets shows that SKSA has higher recall rate, and can match the user´s query intention better.
  • Keywords
    XML; query processing; SKSA; SLCA; XML documents; XML keyword query algorithm based-on-semantic; XML retrieval technology; data node identification; keyword search; node semantic information; recall rate; semantic information; smallest-lowest common ancestor; structural semantic; subtrees; user query intention matching; Databases; Dictionaries; Keyword search; Search engines; Semantics; XML; keyword search; semantic; synonyms; wordnet; xml;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Cloud Computing Companion (ISCC-C), 2013 International Conference on
  • Conference_Location
    Guangzhou
  • Type

    conf

  • DOI
    10.1109/ISCC-C.2013.120
  • Filename
    6973691