The efficiency of suggested keywords and queries among the retrieved sources in PubMed: medical users’ viewpoint in Bushehr University of Medical Sciences
Subject Areas : Journal of Information Systems and ServicesAbdolrasoul Khosravi 1 , Zahra Poosh 2 , Shole Arastoopoor 3
1 - Assistant Professor of Medical Library and Information Sciences, Bushehr University of Medical Sciences
2 - MA Student of Library and Information of Medical Sciences, , Bushehr University of Medical Sciences
3 - Assistant Professor of Regional Information Center for Science and Technology
Keywords: suggested keywords/ user keywo,
Abstract :
Purpose: Medical users face some difficulties in formulating a correct search query while they want to quest in an information retrieval system. To solve this problem, PubMed has added some suggested keywords and queries to its own interface. This research studies the efficiency of these suggested keywords and queries among the retrieved sources in PubMed database from the viewpoint of medical users in Bushehr University of Medical Sciences. Methodology: The populations of this study include MSc students, professional medical students, and faculty members who have had an approved proposal. According to the purpose of the study and using a systematic non probability sampling 40 users selected as the sample study. Findings: The results show that 53 percent of suggested keywords and queries in PubMed have a complete relevancy with initial queries of users. Furthermore, there is not a significant difference between the users’ keywords and the suggested keywords in PubMed. Results: Suggested keywords and queries are an appropriate strategy to access relevant sources which can satisfy users’ need.
خسروی، عبدالرسول (1390). بررسی کارآمدی عبارتهای پیشنهادی موتورهای کاوش در بسط جستجو از دیدگاه کاربران بر اساس اصل کمترین کوشش و نظریه بار شناختی. پایاننامه دوره دکترای کتابداری و اطلاعرسانی. دانشگاه فردوسی مشهد.
فتاحی، رحمتالله (1385). شناسایی و تحلیل واژگان عمومی در منابع وب: رویکردی نو به بسط عبارت جستجو با استفاده از زبان طبیعی در موتورهای کاوش. مطالعاتتربیتیوروانشناسی؛ 7(1): 31-52.
نیکزمان، امیر و فتاحی، رحمتالله (1391). تحلیل بسط عبارتهای جستجوی موضوعی دانشجویان، الگوهای بسط و همخوانی آنها با سرعنوانهای موضوعی فارسی در فهرست رایانهای. پژوهشنامه کتابداری و اطلاعرسانی؛ 2(1): 195-214.
Tang, M. C., Wu, W. C., & Hung, B. W. 2009. Evaluating a metadata‐ based term suggestion interface for PubMed with real users with real requests. Proceedings of the American Society for Information Science and Technology, 46(1), 1-18.
Tuan, L. A., & Kim, J.-j. 2012. Automatic Suggestion for PubMed Query Reformulation. Journal of Computing Science and Engineering, 6(2), 161-167. Cui, H., Wen, J.-R., Nie, J.-Y., & Ma, W.-Y. 2003. Query expansion by mining user logs. Knowledge and Data Engineering, IEEE Transactions on, 15(4), 829-839.
Dogan, R. I., Murray, G. C., Névéol, A., & Lu, Z. 2009. Understanding PubMed® user search behavior through log analysis. Database: the journal of biological databases and curation.
Durao, F., Bayyapu, K., Xu, G., Dolog, P., & Lage, R. 2011. Using tag-neighbors for query expansion in medical information retrieva
Multimedia Tools and Applications,July 2014, Volume 71, Issue 2, pp 905-929
Efthimiadis, E. N. 2000. Interactive query expansion: A user‐based evaluation in a relevance feedback environment. Journal of the American Society for Information Science, 51(11), 989-1003.
Galbiati, G. 1991. A phrase‐based matching function. Journal of the American Society for Information Science, 42(1), 36-48.
Kahn, T. J., & Ninomiya, H. 2003. Changing vocabularies: A guide to help bioethics searchers find relevant literature in National Library of Medicine databases using the Medical Subject Headings (MeSH) indexing vocabulary. Kennedy Institute of Ethics Journal, 13(3), 275-311.
Liu, Z., Natarajan, S., & Chen, Y. 2011. Query expansion based on clustered results. Proceedings of the VLDB Endowment, 4(6), 350-361.
Lu, Z., Kim, W., & Wilbur, W. J. 2009. Evaluation of query expansion using MeSH in PubMed. Information retrieval, 12(1), 69-80.
Nahin, Annette M. 2009.New for PubMed®: Auto Suggest and Titles with Your Search Terms. NLM technical Bulletin, N.370. Retrieved from http://www.nlm.nih.gov/pubs/techbull/so09/so09_pm_autosuggest.html
Niu, Xi, & Kelly, Diane (2014). The use of query suggestions during information search. Information Processing and Management, 50: 218–234.
PubMed Basics. 2012. Pubmed Basics. Staff NLM. Retrieved from Revised May 2012
Song, Y., & He, L.-w. 2010. Optimal rare query suggestion with implicit user feedback. Paper presented at the Proceedings of the 19th international conference on World wide web.