• DocumentCode
    2787208
  • Title

    Mining Customer Feedbacks for Actionable Intelligence

  • Author

    Dey, Lipika ; Haque, Sk Mirajul ; Raj, Nidhi

  • Author_Institution
    TCS Innovation Labs. Delhi, Delhi, India
  • Volume
    3
  • fYear
    2010
  • fDate
    Aug. 31 2010-Sept. 3 2010
  • Firstpage
    239
  • Lastpage
    242
  • Abstract
    Mining consumer-generated text can provide business intelligence to organizations by extracting important knowledge trapped in the form of opinions, thoughts, and ideas expressed by their employees and customers on various aspects relevant to business. The key challenge here is to extract and organize relevant information from noisy text in order to effectively transform it to actionable intelligence. However, there is no formal framework to guide this analytical task. In this work, we present a system that is suitable for purpose-driven mining of free-text customer feedback to convert the knowledge gained to actionable intelligence.
  • Keywords
    Internet; competitive intelligence; customer satisfaction; knowledge acquisition; organisational aspects; text analysis; actionable intelligence; business intelligence; consumer generated text Mining; free text customer feedback mining; knowledge extraction; purpose driven mining; Accuracy; Business; Feature extraction; Noise measurement; Ontologies; Text mining; Actionable intelligence; Fuzzy clustering; Noisy text; Ontology; Opinion mining; Text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on
  • Conference_Location
    Toronto, ON
  • Print_ISBN
    978-1-4244-8482-9
  • Electronic_ISBN
    978-0-7695-4191-4
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2010.196
  • Filename
    5617332