• DocumentCode
    633121
  • Title

    Web product ranking using opinion mining

  • Author

    Yin-Fu Huang ; Heng Lin

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Yunlin Univ. of Sci. & Technol., Yunlin, Taiwan
  • fYear
    2013
  • fDate
    16-19 April 2013
  • Firstpage
    184
  • Lastpage
    190
  • Abstract
    Online shopping is becoming increasingly important as more and more manufacturers sell products on the Internet, and many users are using the Internet to express and share their opinions. However, it is impossible for consumers to read all product reviews. Therefore, it is necessary to design effective systems to summarize the pros and cons of product characteristics, so that consumers can quickly find their favorable products. In this paper, we present a product ranking system using opinion mining techniques. Users can specify product features to get back the ranking results of all matched products. In this system, we consider three issues while calculating product scores: 1) product reviews, 2) product popularity, and 3) product release month. Finally, the experimental results show that the system is practical and the ranking results are interesting.
  • Keywords
    Internet; data mining; information retrieval; pattern classification; retail data processing; Internet; Web product ranking system; online shopping; opinion mining techniques; product popularity; product ranking system; product release month; product reviews; product score; Data mining; HTML; Internet; Tagging; User interfaces; XML; POS; XML document; information retrieval; opinion mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Data Mining (CIDM), 2013 IEEE Symposium on
  • Conference_Location
    Singapore
  • Type

    conf

  • DOI
    10.1109/CIDM.2013.6597235
  • Filename
    6597235