• DocumentCode
    3425150
  • Title

    Learning contextual behavior of text data

  • Author

    Bayrak, Coskun ; Joshi, Hemant

  • Author_Institution
    Dept. of Comput. Sci., Arkansas Univ., Little Rock, AR, USA
  • fYear
    2005
  • fDate
    15-17 Dec. 2005
  • Abstract
    Understanding contextual behavior is very important in order to develop a context-aware retrieval system. This paper discusses the philosophy behind the development of the "evolutionary behavior of textual semantics" (EBOTS) system. The EBOTS system is retrieval oriented knowledge representation and management system. This paper proposes a formal model of correlation that can be combined with traditional local and global weighing schemes. Intuitive contextual behavior is studied as a part of proposed research work. Context retrieval based on semantic knowledge allows abstract queries to be defined, instead of exact word-based queries. The results of the context retrieval for a classic3 and time dataset using the EBOTS system have been discussed in this paper. The paper makes a contribution to the semantic knowledge representation and retrieval algorithms.
  • Keywords
    formal specification; knowledge representation; learning (artificial intelligence); programming language semantics; query formulation; text analysis; abstract query; context aware retrieval system; evolutionary behavior; formal model; global weighing scheme; intuitive contextual behavior; management system; retrieval algorithm; semantic knowledge representation; text data; textual semantics; word based query; Computer science; Context modeling; Costs; Information retrieval; Knowledge management; Knowledge representation; Natural language processing; Natural languages; Text analysis; Web sites;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications, 2005. Proceedings. Fourth International Conference on
  • Print_ISBN
    0-7695-2495-8
  • Type

    conf

  • DOI
    10.1109/ICMLA.2005.46
  • Filename
    1607466