Retrieval feedback in MEDLINE. Export

@article{Srinivasan_JAMIA_1996, abstract = {OBJECTIVE: To investigate a new approach for query expansion based on retrieval feedback. The first objective in this study was to examine alternative query-expansion methods within the same retrieval-feedback framework. The three alternatives proposed are: expansion on the MeSH query field alone, expansion on the free-text field alone, and expansion on both the MeSH and the free-text fields. The second objective was to gain further understanding of retrieval feedback by examining possible dependencies on relevant documents during the feedback cycle. DESIGN: Comparative study of retrieval effectiveness using the original unexpanded and the alternative expanded user queries on a MEDLINE test collection of 75 queries and 2,334 MEDLINE citations. MEASUREMENTS: Retrieval effectivenesses of the original unexpanded and the alternative expanded queries were compared using 11-point-average precision scores (11-AvgP). These are averages of precision scores obtained at 11 standard recall points. RESULTS: All three expansion strategies significantly improved the original queries in terms of retrieval effectiveness. Expansion on MeSH alone was equivalent to expansion on both MeSH and the free-text fields. Expansion on the free-text field alone improved the queries significantly less than did the other two strategies. The second part of the study indicated that retrieval-feedback-based expansion yields significant performance improvements independent of the availability of relevant documents for feedback information. CONCLUSIONS: Retrieval feedback offers a robust procedure for query expansion that is most effective for MEDLINE when applied to the MeSH field.}, address = {Department of Computer Science, Cornell University, Ithaca, NY, USA. padmini-srinivasan@uiowa.edu}, author = {Srinivasan, P.}, citeulike-article-id = {2447083}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/8653452}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=8653452}, issn = {1067-5027}, journal = {Journal of the American Medical Informatics Association : JAMIA}, keywords = {health, ir, medline}, number = {2}, pages = {157--167}, posted-at = {2009-11-09 22:32:55}, priority = {2}, title = {Retrieval feedback in MEDLINE.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/8653452}, volume = {3}, year = {1996} }

TY - JOUR ID - Srinivasan_JAMIA_1996 L3 - citeulike-article-id:2447083 N2 - OBJECTIVE: To investigate a new approach for query expansion based on retrieval feedback. The first objective in this study was to examine alternative query-expansion methods within the same retrieval-feedback framework. The three alternatives proposed are: expansion on the MeSH query field alone, expansion on the free-text field alone, and expansion on both the MeSH and the free-text fields. The second objective was to gain further understanding of retrieval feedback by examining possible dependencies on relevant documents during the feedback cycle. DESIGN: Comparative study of retrieval effectiveness using the original unexpanded and the alternative expanded user queries on a MEDLINE test collection of 75 queries and 2,334 MEDLINE citations. MEASUREMENTS: Retrieval effectivenesses of the original unexpanded and the alternative expanded queries were compared using 11-point-average precision scores (11-AvgP). These are averages of precision scores obtained at 11 standard recall points. RESULTS: All three expansion strategies significantly improved the original queries in terms of retrieval effectiveness. Expansion on MeSH alone was equivalent to expansion on both MeSH and the free-text fields. Expansion on the free-text field alone improved the queries significantly less than did the other two strategies. The second part of the study indicated that retrieval-feedback-based expansion yields significant performance improvements independent of the availability of relevant documents for feedback information. CONCLUSIONS: Retrieval feedback offers a robust procedure for query expansion that is most effective for MEDLINE when applied to the MeSH field. IS - 2 JF - Journal of the American Medical Informatics Association : JAMIA SN - 1067-5027 AD - Department of Computer Science, Cornell University, Ithaca, NY, USA. padmini-srinivasan@uiowa.edu EP - 167 TI - Retrieval feedback in MEDLINE. VL - 3 SP - 157 KW - health KW - ir KW - medline AU - Srinivasan, P PY - 1996///r UR - http://view.ncbi.nlm.nih.gov/pubmed/8653452 ER -