• DocumentCode
    2656994
  • Title

    Design analysis and implementation for ontology learning model

  • Author

    Yang, Qing ; Cai, Kai-min ; Sun, Jun-Li ; Li, Yan

  • Author_Institution
    Dept. of Comput. Sci., Huazhong Normal Univ., Wuhan, China
  • Volume
    3
  • fYear
    2010
  • fDate
    16-18 April 2010
  • Abstract
    Ontology learning is a technology. Ontology learning can be used to establish ontology automatically or semi-automatically by introducing the ontology engineering and machine learning technology and many other sciences and technologies. The ontology learning technology which is proposed in our paper is to reduce the time of building an entire ontology. Our paper presents an Ontology Learning model which will enhance the efficiency of extraction concept, and enhance the efficiency of ontology building. It includes several aspects, and area concept extraction is the main aspect of all. The model combines personalized recommendation with concept extraction and realizes a more accurate and stable domain concept extraction method. We describe these techniques and report the results of the experiment examining its effectiveness and efficiency.
  • Keywords
    learning (artificial intelligence); ontologies (artificial intelligence); area concept extraction; design analysis; extraction concept; machine learning; ontology building; ontology engineering; ontology learning model; personalized recommendation; stable domain concept extraction; Collaboration; Computer science; Data mining; Filtering; Learning systems; Machine learning; Ontologies; Paper technology; Statistical analysis; Sun; concept extraction; learning; ontology; personalization ecommendation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-6347-3
  • Type

    conf

  • DOI
    10.1109/ICCET.2010.5485818
  • Filename
    5485818