Efficient set joins on similarity predicates
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
SVD based Term Suggestion and Ranking System
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Keyword Generation for Search Engine Advertising
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Keyword generation for search engine advertising using semantic similarity between terms
Proceedings of the ninth international conference on Electronic commerce
Learning query intent from regularized click graphs
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Optimizing relevance and revenue in ad search: a query substitution approach
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Web-scale distributional similarity and entity set expansion
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Automatic generation of bid phrases for online advertising
Proceedings of the third ACM international conference on Web search and data mining
From frequency to meaning: vector space models of semantics
Journal of Artificial Intelligence Research
Searchable web sites recommendation
Proceedings of the fourth ACM international conference on Web search and data mining
Web-scale table census and classification
Proceedings of the fourth ACM international conference on Web search and data mining
Intent feature discovery using Q&A corpus and web data
Proceedings of the 4th International Conference on Uniquitous Information Management and Communication
Automatic generation of listing ads by reusing promotional texts
Proceedings of the 12th International Conference on Electronic Commerce: Roadmap for the Future of Electronic Business
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In online advertising, pervasive in commercial search engines, advertisers typically bid on few terms, and the scarcity of data makes ad matching difficult. Suggesting additional bidterms can significantly improve ad clickability and conversion rates. In this paper, we present a large-scale bidterm suggestion system that models an advertiser's intent and finds new bidterms consistent with that intent. Preliminary experiments show that our system significantly increases the coverage of a state of the art production system used at Yahoo while maintaining comparable precision.