Incremental Relevance Feedback in Japanese Text Retrieval

@article{Jones:00, abstract = {The application of relevance feedback techniques has been shown to improve retrieval performance for a number of information retrieval tasks. This paper explores incremental relevance feedback for ad hoc Japanese text retrieval; examining, separately and in combination, the utility of term reweighting and query expansion using a probabilistic retrieval model. Retrieval performance is evaluated in terms of standard precision-recall measures, and also using “number-to-view” graphs. Experimental results, on the standard BMIR-J2 Japanese language retrieval collection, show that both term reweighting and query expansion improve retrieval performance. This is reflected in improvements in both precision and recall, but also a reduction in the average number of documents which must be viewed to find a selected number of relevant items. In particular, using a simple simulation of user searching, incremental application of relevance information is shown to lead to progressively improved retrieval performance and an overall reduction in the number of documents that a user must view to find relevant ones.}, author = {Jones, Gareth and Sakai, Tetsuya and Kajiura, Masahiro and Sumita, Kazuo }, citeulike-article-id = {2817027}, doi = {http://dx.doi.org/10.1023/A:1009932512781}, journal = {Information Retrieval}, keywords = {relevance-feedback}, month = {May}, number = {4}, pages = {361--384}, posted-at = {2008-05-20 16:55:55}, priority = {2}, title = {Incremental Relevance Feedback in Japanese Text Retrieval}, url = {http://dx.doi.org/10.1023/A:1009932512781}, volume = {2}, year = {2000} }

TY - JOUR ID - Jones:00 L3 - citeulike-article-id:2817027 TI - Incremental Relevance Feedback in Japanese Text Retrieval JF - Information Retrieval VL - 2 IS - 4 SP - 361 EP - 384 N2 - The application of relevance feedback techniques has been shown to improve retrieval performance for a number of information retrieval tasks. This paper explores incremental relevance feedback for ad hoc Japanese text retrieval; examining, separately and in combination, the utility of term reweighting and query expansion using a probabilistic retrieval model. Retrieval performance is evaluated in terms of standard precision-recall measures, and also using “number-to-view” graphs. Experimental results, on the standard BMIR-J2 Japanese language retrieval collection, show that both term reweighting and query expansion improve retrieval performance. This is reflected in improvements in both precision and recall, but also a reduction in the average number of documents which must be viewed to find a selected number of relevant items. In particular, using a simple simulation of user searching, incremental application of relevance information is shown to lead to progressively improved retrieval performance and an overall reduction in the number of documents that a user must view to find relevant ones. KW - relevance-feedback AU - Jones, Gareth AU - Sakai, Tetsuya AU - Kajiura, Masahiro AU - Sumita, Kazuo PY - 2000/05/01/ UR - http://dx.doi.org/10.1023/A:1009932512781 ER -