Ranking of field association terms using Co-word analysis

  • Authors:

  • Mahmoud Rokaya;Elsayed Atlam;Masao Fuketa;Tshering C. Dorji;Jun-ichi Aoe

  • Affiliations:

  • Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima 770-8506, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima 770-8506, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima 770-8506, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima 770-8506, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima 770-8506, Japan

  • Venue:
  • Information Processing and Management: an International Journal
  • Year:
  • 2008

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Abstract

Information retrieval involves finding some desired information in a store of information or a database. In this paper, Co-word analysis will be used to achieve a ranking of a selected sample of FA terms. Based on this ranking a better arranging of search results can be achieved. Experimental results achieved using 41MB of data (7660 documents) in the field of sports. The corpus was collected from CNN newspaper, sports field. This corpus was chosen to be distributed over 11 sub-fields of the field sports from the experimental results, the average precision increased by 18.3% after applying the proposed arranging scheme depending on the absolute frequency to count the terms weights, and the average precision increased by 17.2% after applying the proposed arranging scheme depending on a formula based on ''TF*IDF'' to count the terms weights.