Using UMLS-based Re-Weighting Terms as a Query Expansion Strategy, accepted by
| Venue: | IEEE International Conference on Granular Computing , May10-12, 2006 |
| Citations: | 2 - 2 self |
BibTeX
@INPROCEEDINGS{Zhu_usingumls-based,
author = {Weizhong Zhu and Xuheng Xu and Xiaohua Hu and Il-yeol Song and Robert B. Allen},
title = {Using UMLS-based Re-Weighting Terms as a Query Expansion Strategy, accepted by},
booktitle = {IEEE International Conference on Granular Computing , May10-12, 2006},
year = {}
}
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Abstract
Abstract—Search engines have significantly improved the efficiency of bio-medical literature searching. These search engines, however, could return many irrelevant results to the intention of the user’s query. To improve precision and recall, various query expansion strategies are widely used. In this paper, we explore the three widely used query expansion strategies-local analysis, global analysis, and ontology-based term reweighting across various search engines. Through experiments, we show that ontology-based term re-weighting works best. Term re-weighting reformulates queries with selection of key original query terms and re-weights these terms and their associated synonyms from UMLS. The results of experiments show that with LUCENE and LEMUR, the average precision is enhanced by up to 20.3 % and 12.1%, respectively, compared to the baseline runs. We believe the principles of this term re-weighting strategy may be extended and utilized in other bio-medical domains. Index Terms—query expansion strategy, term re-weighting, UMLS, ontology I.
