• DocumentCode
    3254175
  • Title

    Concepts extraction for medical documents using ontology

  • Author

    Mala, Vajenti ; Lobiyal, D.K.

  • Author_Institution
    Sch. of Comput. & Syst. Sci., Jawaharlal Nehru Univ., New Delhi, India
  • fYear
    2015
  • fDate
    19-20 March 2015
  • Firstpage
    773
  • Lastpage
    777
  • Abstract
    In the biomedical domain large amount of text documents are unstructured information is available in digital text form. Text Mining is the method or technique to find for interesting and useful information from unstructured text. Text Mining is also an important task in medical domain. The technique uses for Information retrieval, Information extraction and natural language processing (NLP). Traditional approaches for information retrieval are based on key based similarity. These approaches are used to overcome these problems; Semantic text mining is to discover the hidden information from unstructured text and making relationships of the terms occurring in them. In the biomedical text, the text should be in the form of text which can be present in the books, articles, literature abstracts, and so forth. Most of information is stored in the text format, so in this paper we will focus on the role of ontology for semantic text mining by using WordNet. Specifically, we have presented a model for extracting concepts from text documents using linguistic ontology in the domain of medical.
  • Keywords
    document handling; information retrieval; medical administrative data processing; medical computing; natural language processing; ontologies (artificial intelligence); NLP; WordNet; biomedical domain; concept extraction; digital text; hidden information; information extraction; information retrieval; linguistic ontology; medical documents; medical domain; natural language processing; semantic text mining; text documents; text mining; unstructured information; unstructured text; Cancer; Clustering algorithms; Diseases; Information retrieval; Ontologies; Semantics; Text mining; Concept cluster; English WordNet; Information retrieval; Semantic relations; Text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in
  • Conference_Location
    Ghaziabad
  • Type

    conf

  • DOI
    10.1109/ICACEA.2015.7164807
  • Filename
    7164807