• DocumentCode
    2132067
  • Title

    Interactive Exploration of Model-Based Automatically Extracted Data

  • Author

    Coden, Anni ; Sominsky, Igor ; Tanenblatt, Michael

  • Author_Institution
    T.J. Watson Res. Center, IBM, Hawthorne, NY
  • fYear
    2008
  • fDate
    15-19 Dec. 2008
  • Firstpage
    967
  • Lastpage
    970
  • Abstract
    We present an interactive system to query, explore and navigate data according to a hierarchical knowledge model that had been automatically populated from unstructured textual data. Our system differs from systems assisting in the navigation of domain ontologies and mining between pairs of concepts in that it enables access to unstructured data by abstract concepts and relations between them. Concepts in turn are specified by sets of models and their relations. However, some concepts may not have a direct representation in the text. In particular, the demonstration query by model/cancer (QbM/C) is based on unstructured pathology reports. The knowledge model represents both named entities such as diagnosis and anatomical site, and higher level concepts such as primary and metastatic tumor. Such concepts are based on the relations between named entities. We will present the data layout and access mechanism from the GUI to the data.
  • Keywords
    data mining; feature extraction; graphical user interfaces; medical computing; ontologies (artificial intelligence); query processing; GUI; access mechanism; data layout; data navigation; domain ontologies; hierarchical knowledge model; interactive exploration; metastatic tumor; model-based automatic data extraction; unstructured textual data; Cancer; Colon; Data mining; Diseases; Lymph nodes; Medical diagnostic imaging; Metastasis; Navigation; Neoplasms; Pathology; data model; information extraction; medical knowledge representation; search and browse;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshops, 2008. ICDMW '08. IEEE International Conference on
  • Conference_Location
    Pisa
  • Print_ISBN
    978-0-7695-3503-6
  • Electronic_ISBN
    978-0-7695-3503-6
  • Type

    conf

  • DOI
    10.1109/ICDMW.2008.34
  • Filename
    4734029