Volume 5, Issue 3 (12-2018)
Human Information Interaction 2018, 5(3): 1-14 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
karimi E, Babaee M, Hosseini Beheshti M. Analysis of User query refinement behavior based on semantic features: user log analysis of Ganj database (IranDoc). Human Information Interaction 2018; 5 (3)
URL: http://hii.khu.ac.ir/article-1-2800-en.html
URL: http://hii.khu.ac.ir/article-1-2800-en.html
Iranian Research Institute for Information Science and Technology
Abstract: (7960 Views)
Background and Aim: Information systems cannot be well designed or developed without a clear understanding of needs of users, manner of their information seeking and evaluating. This research has been designed to analyze the Ganj (Iranian research institute of science and technology database) users’ query refinement behaviors via log analysis.
Methods: The method of this research is log analysis. In this research, the Ganj users’ query refinement behaviors were analyzed. User’s logs during 3 months between May and June 2016 were analyzed for semantic features. The study tool was a researcher-made checklist of semantic features. The total searches were 10 milion records which were limited to information science domain. About 106641 records were selected for analysis.
Results: The semantic relationships (based on thesaurus relationships) were revealed between pair’s terms in user’s searches. The results showed that users refined their searches based on some semantic relationships.
Conclusion: The results of this research can be used to improve the Ganj results and for term suggestion for users, so that they be able to choose proper terms while there are several related terms.
Methods: The method of this research is log analysis. In this research, the Ganj users’ query refinement behaviors were analyzed. User’s logs during 3 months between May and June 2016 were analyzed for semantic features. The study tool was a researcher-made checklist of semantic features. The total searches were 10 milion records which were limited to information science domain. About 106641 records were selected for analysis.
Results: The semantic relationships (based on thesaurus relationships) were revealed between pair’s terms in user’s searches. The results showed that users refined their searches based on some semantic relationships.
Conclusion: The results of this research can be used to improve the Ganj results and for term suggestion for users, so that they be able to choose proper terms while there are several related terms.
Send email to the article author
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
