• DocumentCode
    3582130
  • Title

    ProRankSys: Ranking consumer products by predicting opinion´s weight on reviews

  • Author

    Arun Manicka Raja, M. ; Winster, S. Godfrey ; Saravanan, R. ; Swamynathan, S.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Saveetha Eng. Coll., Chennai, India
  • fYear
    2014
  • Firstpage
    33
  • Lastpage
    38
  • Abstract
    The advancement of web has empowered e-commerce facilities and induced the intimidation of physical stores gradually. The online shopping space is growing all over the world. The consumers who mainly shop for products or services, before purchasing they wish to check for the product reviews that have been commented by other consumers. Therefore, analyzing the consumer reviews of online shopping is important to ease the future consumer´s purchase. Generally, review analysis involves the process of determining the opinion polarity and then providing the results of performed analysis to the users by suggesting better products to users. Though various existing research methods are available for performing product analysis, it is important to reveal the individual opinion´s weight by predicting the strength of each reviews and assessing the overall rank of the product by consolidating the predicted review strength. Therefore, the Online consumers can find out the reviews what they intended to attain quickly without searching all the reviews. The experimental result show that the proposed work yields better recommendation on products.
  • Keywords
    Internet; electronic commerce; retail data processing; ProRankSys; World Wide Web; consumer products ranking; e-commerce facilities; online consumers; online shopping; Computers; Conferences; Consumer products; Crawlers; Data mining; Feature extraction; Ontologies; crawler; featured reviews; fuzzy; ontology; opinion mining; ranking; review weight;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Communication and Systems, 2014 International Conference on
  • Print_ISBN
    978-1-4799-3671-7
  • Type

    conf

  • DOI
    10.1109/ICCCS.2014.7068163
  • Filename
    7068163