• DocumentCode
    658642
  • Title

    Text-Driven Multi-structured Data Analytics for Enterprise Intelligence

  • Author

    Dey, Lipika ; Verma, Ishan

  • Author_Institution
    TCS Innovation Labs., Tata Consultancy Services, New Delhi, India
  • Volume
    3
  • fYear
    2013
  • fDate
    17-20 Nov. 2013
  • Firstpage
    213
  • Lastpage
    220
  • Abstract
    Text data constitutes the bulk of all enterprise data. Text repositories are not only tacit store-houses of knowledge about its people, projects and processes but also contain invaluable information about its customers, competitors, suppliers, partners and all other stakeholders. Mining this data can provide interesting and valuable insights provided it is appropriately integrated with other enterprise data. In this paper we propose a framework for text-driven analysis of multi-structured data.
  • Keywords
    business data processing; competitive intelligence; data analysis; data mining; text analysis; data mining; enterprise data; enterprise intelligence; text data; text driven analysis; text driven multistructured data analytics; text repositories; Business; Context; Media; Natural language processing; Semantics; Text mining; Information Fusion; Text Analytics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013 IEEE/WIC/ACM International Joint Conferences on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    978-1-4799-2902-3
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2013.186
  • Filename
    6690731
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=658642