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  • 标题:Evaluation of using expert system features in information retrieval in Iranian digital library software
  • 本地全文:下载
  • 作者:Shahbazi, Farzad ; Norouzi, Yaghoub ; Alipour-Hafezi, Mehdi
  • 期刊名称:Iranian Journal of Information Processing & Management
  • 印刷版ISSN:2251-8223
  • 电子版ISSN:2251-8231
  • 出版年度:2015
  • 卷号:30
  • 期号:3
  • 页码:823-851
  • 出版社:Iranian Research Institute for Information and Technology
  • 摘要:The goal of this study is to evaluate expert system features in Iranian’s selected Digital Library software in context of information retrieval. Methodology: This study was performed using evolutional method and whit a checklist. To gathering data, a checklist was prepared by 66 criteria based of the research dimensions (include Tools of information retrieval, Interface, Information database (Knowledge), and the strategies used for the more guidance of users). Furthermore, we took the opinion of LIS expert in necessity. The population in this study was 5 selected Iranian Digital Library software’s include Pars Azarakhsh, Simorgh, Papyrus, Payam and Parvan. Finding: The status of the selected Digital library software’s investigated based on research dimensions. According to the studied criteria in research, the results showed that selected digital library software’s are lower than normal in matter of information recovery and information data base, but in the interface feature is higher than normal range. Also in the more guidance of user’s dimensions, result showed that the most emphasis is in common software features instead of specialized of them. Hypothesis test also showed that there is significant difference between features of the expert system software current status of digital libraries, in Iran. Originality/Value: The research prepared a checklist for evaluation of Digital Library software’s in expert systems context. Also the funded results can be helpful for the software providers to resolve the weakness and reinforce the strengths of software’s.
  • 关键词:Library software ; Digital library ; Information retrieval ; Expert system ; Evaluation studies ; Evaluation criteria
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