• DocumentCode
    2261395
  • Title

    An Intelligent Text Mining System Applied to SEC Documents

  • Author

    Zheng, Ying ; Zhou, Harry

  • fYear
    2012
  • fDate
    May 30 2012-June 1 2012
  • Firstpage
    155
  • Lastpage
    160
  • Abstract
    This paper presents an intelligent corporate governance analysis and rating system, called ICGA, capable of retrieving SEC required documents of public companies and performing analysis and rating in terms of recommended corporate governance practices. With local knowledge bases, databases, and semantic networks, ICGA is able to automatically evaluate the strengths, deficiencies, and risks of a company´s corporate governance practices and board of directors based on the documents stored in the SEC EDGAR database. The produced score reduces a complex corporate governance process and related policies into a single number which enables concerned government agencies, investors and legislators to assess the governance characteristics of individual companies.
  • Keywords
    corporate modelling; data mining; information retrieval; knowledge based systems; semantic networks; text analysis; ICGA; SEC EDGAR database; SEC document retrieval; Securities and Exchange Commission; governance characteristics; government agencies; intelligent corporate governance analysis; intelligent text mining system; investors; legislators; local knowledge bases; public companies; rating system; recommended corporate governance practices; semantic networks; Companies; Databases; Industries; Knowledge based systems; Manuals; Semantics; Standards; Semantic net; information retrieval; knowledge base; text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Science (ICIS), 2012 IEEE/ACIS 11th International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4673-1536-4
  • Type

    conf

  • DOI
    10.1109/ICIS.2012.124
  • Filename
    6211818