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EMNLP
2009

Empirical Exploitation of Click Data for Task Specific Ranking

10 years 11 days ago
Empirical Exploitation of Click Data for Task Specific Ranking
There have been increasing needs for task specific rankings in web search such as rankings for specific query segments like long queries, time-sensitive queries, navigational queries, etc; or rankings for specific domains/contents like answers, blogs, news, etc. In the spirit of "divide-andconquer", task specific ranking may have potential advantages over generic ranking since different tasks have task-specific features, data distributions, as well as featuregrade correlations. A critical problem for the task-specific ranking is training data insufficiency, which may be solved by using the data extracted from click log. This paper empirically studies how to appropriately exploit click data to improve rank function learning in task-specific ranking. The main contributions are 1) the exploration on the utilities of two promising approaches for click pair extraction; 2) the analysis of the role played by the noise information which inevitably appears in click data extraction; 3...
Anlei Dong, Yi Chang, Shihao Ji, Ciya Liao, Xin Li
Added 17 Feb 2011
Updated 17 Feb 2011
Type Journal
Year 2009
Where EMNLP
Authors Anlei Dong, Yi Chang, Shihao Ji, Ciya Liao, Xin Li, Zhaohui Zheng
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