Proceedings of the 6th international conference on Intelligent user interfaces
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Machine Learning for Sequential Data: A Review
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
An Efficient Boosting Algorithm for Combining Preferences
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Query type classification for web document retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
Evaluating implicit measures to improve web search
ACM Transactions on Information Systems (TOIS)
Automatic identification of user goals in Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Accurately interpreting clickthrough data as implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Learning to rank using gradient descent
ICML '05 Proceedings of the 22nd international conference on Machine learning
Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Incorporating query difference for learning retrieval functions in world wide web search
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Learning to rank: from pairwise approach to listwise approach
Proceedings of the 24th international conference on Machine learning
Learn from web search logs to organize search results
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Varying approaches to topical web query classification
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Supporting intelligent Web search
ACM Transactions on Internet Technology (TOIT)
Active exploration for learning rankings from clickthrough data
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Ranking refinement and its application to information retrieval
Proceedings of the 17th international conference on World Wide Web
Query dependent ranking using K-nearest neighbor
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Learning query intent from regularized click graphs
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
How does clickthrough data reflect retrieval quality?
Proceedings of the 17th ACM conference on Information and knowledge management
A dynamic bayesian network click model for web search ranking
Proceedings of the 18th international conference on World wide web
Adapting ranking functions to user preference
ICDEW '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering Workshop
Global ranking by exploiting user clicks
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Here or there: preference judgments for relevance
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Cross-market model adaptation with pairwise preference data for web search ranking
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Ranking function adaptation with boosting trees
ACM Transactions on Information Systems (TOIS)
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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-and-conquer", task specific ranking may have potential advantages over generic ranking since different tasks have task-specific features, data distributions, as well as feature-grade 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) the appropriate strategy for combining training data and click data; 4) the comparison of click data which are consistent and inconsistent with baseline function.