• DocumentCode
    525414
  • Title

    An area concept extraction algorithm based on association rule

  • Author

    Yang, Qing ; Cai, Kai-min ; Li, Yan ; Liu, Rui-qing

  • Author_Institution
    Dept. of Comput. Sci., Hua Zhong Normal Univ., Wuhan, China
  • Volume
    3
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Abstract
    Ontology learning is from a given area document sets automatic or semi-automatic extraction terms to construct a domain ontology. Area concept extraction is one of the most important aspects in building ontology. In this paper, we proposed an improved area concept extraction algorithm. In the algorithm, we firstly employed association rule algorithm to obtain the similarity between the sememes, and then used the similarity between the sememes to find the similarity between area concepts. Finally our paper achieves the whole area concepts extraction process. By analyzing the experimental results shows the effectiveness and correctness of the algorithm.
  • Keywords
    data mining; learning (artificial intelligence); ontologies (artificial intelligence); area concept extraction algorithm; association rule; domain ontology; ontology learning; sememe similarity; Accuracy; Algorithm design and analysis; Association rules; Buildings; Computer science; Data mining; Dictionaries; Educational institutions; Libraries; Ontologies; area concept extraction; association rule; sememe;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Design and Applications (ICCDA), 2010 International Conference on
  • Conference_Location
    Qinhuangdao
  • Print_ISBN
    978-1-4244-7164-5
  • Electronic_ISBN
    978-1-4244-7164-5
  • Type

    conf

  • DOI
    10.1109/ICCDA.2010.5541367
  • Filename
    5541367