Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
Entropy of search logs: how hard is search? with personalization? with backoff?
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
To personalize or not to personalize: modeling queries with variation in user intent
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
Mining rich session context to improve web search
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning semantic categories from clickthrough logs
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Selectively diversifying web search results
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Predicting web searcher satisfaction with existing community-based answers
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Click patterns: an empirical representation of complex query intents
Proceedings of the 21st ACM international conference on Information and knowledge management
On the usefulness of query features for learning to rank
Proceedings of the 21st ACM international conference on Information and knowledge management
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Understanding query ambiguity in web search remains an important open problem. In this paper we reexamine query ambiguity by analyzing the result clickthrough data. Previously proposed clickthrough-based metrics of query ambiguity tend to conflate informational and ambiguous queries. To distinguish between these query classes, we introduce novel metrics based on the entropy of the click distributions of individual searchers. Our experiments over a clickthrough log of commercial search engine demonstrate the benefits of our approach for distinguishing informational from truly ambiguous queries.