Sudip Datta
Vasudeva Varma
ABSTRACT
Verbose web queries are often descriptive in nature where a term based search engine is unable to distinguish between the essential and noisy words, which can result in a drift from the user intent. We present a randomized query reduction technique that builds on an earlier learning to rank based approach. The proposed technique randomly picks only a small set of samples, instead of the exponentially many sub-queries, thus being fast enough to be useful for web search engines, while still covering wide sub-query space.
- http://weblogs.hitwise.com/alan-long/2009/11/searches_getting_longer.html.Google Scholar
- N. Balasubramanian, G. Kumaran, and V. R. Carvalho. Exploring reductions for long web queries. In SIGIR'10. Google ScholarDigital Library
- M. Bendersky and W. B. Croft. Analysis of long queries in a large scale search log. WSCD '09. Google ScholarDigital Library
- T. Joachims. Optimizing search engines using clickthrough data. In KDD '02. Google ScholarDigital Library
- G. Kumaran and V. R. Carvalho. Reducing long queries using query quality predictors. In SIGIR '09. Google ScholarDigital Library
Index Terms
- Tossing coins to trim long queries
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