• DocumentCode
    2768078
  • Title

    Automatic Domain-Ontology Structure and Example Acquisition from Semi-Structured Texts

  • Author

    Xiao, Cheng ; Zheng, Dequan ; Yang, Yuhang

  • Author_Institution
    MOE-MS Key Lab. of Natural Language Process. & Speech, Harbin Inst. of Technol., Harbin, China
  • Volume
    7
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    530
  • Lastpage
    534
  • Abstract
    This paper presents a new method to acquire domain-ontology structure and examples from semi-structured data sources. Firstly, extract domain-ontology structure, including candidate attributes extraction using certain patterns and applying a statistic method to filter out the incorrect attributes. Secondly, using domain-ontology structure as a clue, automatically generate example extraction patterns. Finally, acquire ontology examples taking advantage of the special structure feature of the Web pages. Experiments are carried out in the field of film, the precision of the ontology structure extraction is 83.7%, and the highest recall of the examples extraction reaches 90%. Experimental results demonstrate that the method developed in this paper is fairly efficient.
  • Keywords
    information filtering; knowledge acquisition; ontologies (artificial intelligence); statistical analysis; text analysis; Web page; attribute filtering; attributes extraction; automatic domain-ontology structure; example acquisition; example extraction pattern; ontology structure extraction; semistructured data sources; semistructured text; statistic method; Data mining; Fuzzy systems; Laboratories; Natural language processing; Ontologies; Speech processing; Statistical distributions; Statistics; Terminology; Web pages; example; information extraction; ontology structure; semi-structure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3735-1
  • Type

    conf

  • DOI
    10.1109/FSKD.2009.169
  • Filename
    5360066