• DocumentCode
    768783
  • Title

    Mining Text with Pimiento

  • Author

    Adeva, Juan José García ; Calvo, Rafael

  • Author_Institution
    Sch. of Electr. & Inf. Eng., Sydney Univ., NSW
  • Volume
    10
  • Issue
    4
  • fYear
    2006
  • Firstpage
    27
  • Lastpage
    35
  • Abstract
    To perform analysis, decision-making, and knowledge management tasks, information systems use an increasing amount of unstructured information in the form of text. This data influx, in turn, has spawned a need to improve the text-mining technologies required for information retrieval, filtering, and classification. This article compares some of the options available. In particular, the authors focus on Pimiento, a new object-oriented application framework that lets developers create distributed applications that use machine-learning and statistical techniques to automatically process documents
  • Keywords
    classification; data mining; information retrieval; learning (artificial intelligence); object-oriented programming; statistical analysis; text analysis; Pimiento; decision-making; information classification; information retrieval; information systems; knowledge management tasks; machine-learning; object-oriented application framework; text-mining technologies; unstructured information; Application software; Data mining; Humans; Information analysis; Information management; Information retrieval; Performance analysis; Search engines; Software tools; Text mining; catgeorization; clustering; computational linguistics; information extraction; software frameworks; text mining;
  • fLanguage
    English
  • Journal_Title
    Internet Computing, IEEE
  • Publisher
    ieee
  • ISSN
    1089-7801
  • Type

    jour

  • DOI
    10.1109/MIC.2006.85
  • Filename
    1704753