Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Model-based feedback in the language modeling approach to information retrieval
Proceedings of the tenth international conference on Information and knowledge management
Topic-based document segmentation with probabilistic latent semantic analysis
Proceedings of the eleventh international conference on Information and knowledge management
The Journal of Machine Learning Research
Topic modeling with network regularization
Proceedings of the 17th international conference on World Wide Web
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
To swing or not to swing: learning when (not) to advertise
Proceedings of the 17th ACM conference on Information and knowledge management
Statistical Language Models for Information Retrieval A Critical Review
Foundations and Trends in Information Retrieval
Term-based commercial intent analysis
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Automatic generation of bid phrases for online advertising
Proceedings of the third ACM international conference on Web search and data mining
Improving ad relevance in sponsored search
Proceedings of the third ACM international conference on Web search and data mining
Estimating advertisability of tail queries for sponsored search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Probabilistic first pass retrieval for search advertising: from theory to practice
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
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A fundamental task of sponsored search is how to find the best match between web search queries and textual advertisements. To address this problem, we explicitly characterize the criteria for an advertisement to be a 'good match' to a query from two aspects (it should be relevant with the query from information perspective, and it should be able to capture and satisfy the commercial intent in the query). Correspondingly, we introduce in this paper a mixture language model of two parts: a commercial model which characterizes language bias of commercial intent leveraging on users' clicks on advertisements, and an informational model which is a traditional language model with consideration of the entropy of each word to capture informational relevance. We then introduce a regularized expectation-maximization (EM) algorithm model for parameters estimation, and integrate query commercial intent into the scoring function to boost overall click efficiency. Empirical evaluation shows that our model achieves better performance as compared to a well tuned classical language model and deliberated TFIDF-pLSI model (6% and 5% precision improvement at our operating point in production environment of 30% recall, and 5.3% and 6.3% AUC improvement), and performs superior to the KL Divergence language model for tail queries (0.5% nDCG improvement). Live traffic test shows over 2% CTR lift and 2.5% RPS lift as well.