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MedSearch: a specialized search engine for medical information retrieval
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Conference on Information and Knowledge Management archive
Proceeding of the 17th ACM conference on Information and knowledge management table of contents
Napa Valley, California, USA
SESSION: Industry research track table of contents
Pages 143-152  
Year of Publication: 2008
ISBN:978-1-59593-991-3
Authors
Gang Luo  IBM T.J. Watson Research Center, Hawthorne, NY, USA
Chunqiang Tang  IBM T.J. Watson Research Center, Hawthorne, NY, USA
Hao Yang  IBM T.J. Watson Research Center, Hawthorne, NY, USA
Xing Wei  Yahoo! Inc., Sunnyvale, CA, USA
Sponsors
ACM: Association for Computing Machinery
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

People are thirsty for medical information. Existing Web search engines often cannot handle medical search well because they do not consider its special requirements. Often a medical information searcher is uncertain about his exact questions and unfamiliar with medical terminology. Therefore, he sometimes prefers to pose long queries, describing his symptoms and situation in plain English, and receive comprehensive, relevant information from search results. This paper presents MedSearch, a specialized medical Web search engine, to address these challenges. MedSearch uses several key techniques to improve its usability and the quality of search results. First, it accepts queries of extended length and reforms long queries into shorter queries by extracting a subset of important and representative words. This not only significantly increases the query processing speed but also improves the quality of search results. Second, it provides diversified search results. Lastly, it suggests related medical phrases to help the user quickly digest search results and refine the query. We evaluated MedSearch using medical questions posted on medical discussion forums. The results show that MedSearch can handle various medical queries effectively and efficiently.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Gang Luo: colleagues
Chunqiang Tang: colleagues
Hao Yang: colleagues
Xing Wei: colleagues