• DocumentCode
    3125363
  • Title

    Commodity Classification in Hierarchies

  • Author

    Shen, Jie ; Chen, Cang ; Gao, Ying

  • Author_Institution
    Inf. Eng. Coll., Yangzhou Univ., Yangzhou, China
  • fYear
    2009
  • fDate
    28-29 Dec. 2009
  • Firstpage
    267
  • Lastpage
    269
  • Abstract
    In e-commerce transactions, goods are classified according to the hierarchical structure, which refers to a tree category. In the process of classification, we shall consider the special features. While using brand name for category, for instance, the degree of distinction characteristic of brand is higher. Based on this, we prepare a dictionary of brands for Chinese words segamentatin on one hand and use a kind of "discriminative naive Bayes classifier" model on the other hand. According to our experiment, we can get a result that the Naive bayes classification model is better than standard bayesian one.
  • Keywords
    Bayes methods; electronic commerce; natural language processing; text analysis; word processing; Chinese words segmentation; brand name; commodity classification; discriminative naive Bayes classifier; e-commerce transactions; text classification; Bayesian methods; Classification tree analysis; Data mining; Dictionaries; Information systems; Niobium; Support vector machine classification; Support vector machines; Text categorization; Wireless networks; Commodity Classification; Discriminative Naive Bayes; Text Categorize;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Networks and Information Systems, 2009. WNIS '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3901-0
  • Electronic_ISBN
    978-1-4244-5400-6
  • Type

    conf

  • DOI
    10.1109/WNIS.2009.49
  • Filename
    5381929