• DocumentCode
    3371142
  • Title

    Analysis of syntactic patterns for identification of features from unstructured reviews

  • Author

    Khan, Khairullah ; Baharudin, Baharum B.

  • Author_Institution
    Universiti Teknologi PERONAS Malaysia
  • Volume
    1
  • fYear
    2012
  • fDate
    12-14 June 2012
  • Firstpage
    165
  • Lastpage
    169
  • Abstract
    Collecting consumer opinion about products through web is becoming more popular day by day. The opinion of users is helpful to consumers, retailors, and manufacturers in decision making. Due to the huge number user reviews it is impossible to summarize it. Therefore systems are required for mining consumer reviews data efficiently. Opinion mining is an interesting area of research due to its applications in various fields. One of the challenging issues in this area is the identification of opinion components from unstructured reviews. The work of opinion mining is natural language dependent. Therefore syntactic patterns play a key role in identifying the opinion components. In this paper we have presented analysis of synaptic patterns for products features identification from unstructured reviews. Basically the noun phrases are used for named entity identification; however all noun phrases are not features. The problem is how to restrict the patterns to get the features. After in-depth analysis and evaluation we identify a new pattern which shown comparatively best result.
  • Keywords
    Features Extraction; Opinion Mining; Syntactic Patterns;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent and Advanced Systems (ICIAS), 2012 4th International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4577-1968-4
  • Type

    conf

  • DOI
    10.1109/ICIAS.2012.6306180
  • Filename
    6306180