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Analyzing web text association to disambiguate abbreviation in queries
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Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval table of contents
Singapore, Singapore
POSTER SESSION: Posters group 2: blog, tagging, opinion analysis and web IR table of contents
Pages 751-752  
Year of Publication: 2008
ISBN:978-1-60558-164-4
Authors
Xing Wei  Yahoo! Inc., Sunnyvale, CA, USA
Fuchun Peng  Yahoo! Inc., Sunnyvale, CA, USA
Benoit Dumoulin  Yahoo! Inc., Sunnyvale, CA, USA
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

We introduce a statistical model for abbreviation disambiguation in Web search, based on analysis of Web data resources, including anchor text, click log and query log. By combining evidence from multiple sources, we are able to accurately disambiguate the abbreviation in queries. Experiments on real Web search queries show promising results.




Collaborative Colleagues:
Xing Wei: colleagues
Fuchun Peng: colleagues
Benoit Dumoulin: colleagues