首页    期刊浏览 2024年12月01日 星期日
登录注册

文章基本信息

  • 标题:An Improvement of FA Terms Dictionary using Power Link and Co-Word Analysis
  • 本地全文:下载
  • 作者:El-Sayed Atlam ; Dawlat A. El A.Mohamed ; Fayed Ghaleb
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2018
  • 卷号:9
  • 期号:2
  • DOI:10.14569/IJACSA.2018.090233
  • 出版社:Science and Information Society (SAI)
  • 摘要:Information retrieval involves obtaining some wanted information in a database. In this paper, we used the power link to improve the extracted field association terms from corpus by the proposed algorithm to support the machine to take the right decision and attach the candidate words in their convenient position in dictionary of the field association terms. Power Link is used as a quantitative tool to compute the co-citation relation among two words depending on the co-frequency and distances among instances of the words. In this paper, concept of the Power Link as well as modifications of the rules is used to classify the scientific papers into its proper field. In this paper, instead of whole document, a given document will be divided into three parts, namely, title, abstract and body. A given term will be given a weight that depends on the location of the term inside a specific document. The greatest weight will be given to the title then the abstract then the body, respectively. Results show an improvement in precision, recall and F measure.
  • 关键词:Information retrieval; FA terms; co-word analysis; power link; precision; recall
国家哲学社会科学文献中心版权所有