• DocumentCode
    2340977
  • Title

    Research in concept lattice based automatic document ranking

  • Author

    Jun, Tang ; Du, Ya-Jun ; Shen, Jie-Feng

  • Author_Institution
    Coll. of Comput. & Math.-Phys. Sci., Xihua Univ., Chengdu, China
  • Volume
    9
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    5560
  • Abstract
    The research on similarity for measuring document relevance is an important field in information retrieval. Many researchers are using concept lattice defined in formal concept analysis (FC A) as a basis for measuring query-document relevance in text retrieval, i.e. concept lattice-based ranking (CLR). However, formal concept analysis´s notion of similarity for measuring documents relevance in text retrieval is only based on the shortest path linking the query to the document. It is not well defined. To resolve the problems of this approach, first, we evaluate reasonable different weights of edges in the Hasse diagram based on the conceptual generality or specificity. Second, we present a user profile based on concept lattice, and the algorithm for constructing concept lattice based user profile is provided. Third, we present a combination CLR approach by measuring the similarity among query, user profile and document according to the relation between query and user interest based on concept lattice. Our experiment shows that documents retrieved by our combination CLR approach achieve a higher measure of precision than the traditional CLR approach.
  • Keywords
    information filtering; knowledge representation; pattern clustering; relevance feedback; text analysis; Hasse diagram; automatic document ranking; clustering-based ranking; concept lattice-based ranking; document relevance; formal concept analysis; information filtering; information retrieval; query-document relevance; text retrieval; Educational institutions; Indexing; Information analysis; Information filtering; Information retrieval; Joining processes; Knowledge management; Lattices; Navigation; Vocabulary; Concept lattice-based ranking; Formal Concept Analysis; Information retrieval; clustering-based ranking; concept lattice; information filtering; user profile best-match ranking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527927
  • Filename
    1527927