• DocumentCode
    2394318
  • Title

    The Improved Ontology kNN Algorithm and its Application

  • Author

    Shang, Wenqian ; Zhu, Haibin ; Huang, Houkuan ; Qu, Youli ; Lin, Yongmin

  • Author_Institution
    Sch. of Comput. & Inf. Technol., Beijing Jiaotong Univ.
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    198
  • Lastpage
    203
  • Abstract
    With the advances of the Web, more and more people, especially business people, use emails to communicate with each other. Hence, how to deal with business emails is becoming more and more important for decision makers, because among these emails, there hides valuable information such as the customer´s complaints about a product or the interests of customers to a product. These are important information for a manager to propose marketing policies. In this paper, we develop an improved kNN algorithm - fkNN (fuzzy kNN) algorithm based on ontology ideology to classify the emails. After classifying the emails into different classes, we can mine knowledge more easily based on the classified emails. Therefore, the classification effect is very important for mining knowledge further. Fortunately, our improved algorithm behaves much better than other algorithms in classification performance for our email datasets and other datasets
  • Keywords
    Internet; data mining; electronic commerce; electronic mail; fuzzy neural nets; ontologies (artificial intelligence); Web; business email datasets; decision making; fuzzy kNN algorithm; knowledge mining; ontology ideology; ontology kNN algorithm; Classification algorithms; Companies; Computer science; Government; Information technology; Internet; Ontologies; Support vector machine classification; Support vector machines; World Wide Web;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control, 2006. ICNSC '06. Proceedings of the 2006 IEEE International Conference on
  • Conference_Location
    Ft. Lauderdale, FL
  • Print_ISBN
    1-4244-0065-1
  • Type

    conf

  • DOI
    10.1109/ICNSC.2006.1673142
  • Filename
    1673142