Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
Efficient query evaluation using a two-level retrieval process
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Predicting clicks: estimating the click-through rate for new ads
Proceedings of the 16th international conference on World Wide Web
Extracting structured information from user queries with semi-supervised conditional random fields
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Mining search query logs for spoken language understanding
SDCTD '12 NAACL-HLT Workshop on Future Directions and Needs in the Spoken Dialog Community: Tools and Data
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We present a document expansion approach that uses Conditional Random Field (CRF) segmentation to automatically extract salient phrases from ad titles. We then supplement the ad document with query segments that are probable translations of the document phrases, as learned from a large commercial search engine's click logs. Our approach provides a significant improvement in DCG and interpolated precision and recall on a large set of human labeled query-ad pairs.