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Using UMLS-based re-weighting terms as a query expansion strategy
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1860/1539
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| Title: | Using UMLS-based re-weighting terms as a query expansion strategy |
| Authors: | Zhu, Weizhong
Xu, Xuheng George
Hu, Xiaohua
Song, Il-Yeol
Allen, Robert B. |
| Keywords: | query expansion strategy
pseudo feedback
term re-weighting
UMLS |
| Issue Date: | 2006 |
| Publisher: | IEEE Institute of Electrical and Electronics Engineers |
| Citation: | Paper presented at the 2006 IEEE International Conference on Granular Computing, Atlanta, GA. |
| Abstract: | Search engines have significantly improved the
efficiency of bio-medical literature searching. These search
engines, however, still return many results that are irrelevant to
the intention of a 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 key 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 baseline
runs. We believe the principles of this term re-weighting strategy
may be extended and utilized in other bio-medical domains. |
| URI: | http://hdl.handle.net/1860/1539 |
| Appears in Collections: | Faculty Research and Publications (IST)
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