A maximum entropy approach to natural language processing
Computational Linguistics
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
Keyword generation for search engine advertising using semantic similarity between terms
Proceedings of the ninth international conference on Electronic commerce
Syntactic Information Retrieval
GRC '07 Proceedings of the 2007 IEEE International Conference on Granular Computing
An experimental comparison of click position-bias models
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Online learning from click data for sponsored search
Proceedings of the 17th international conference on World Wide Web
Contextual advertising by combining relevance with click feedback
Proceedings of the 17th international conference on World Wide Web
Modeling and predicting user behavior in sponsored search
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Bayesian Browsing Model: Exact Inference of Document Relevance from Petabyte-Scale Data
ACM Transactions on Knowledge Discovery from Data (TKDD)
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
An analysis of user behavior in online video streaming
Proceedings of the international workshop on Very-large-scale multimedia corpus, mining and retrieval
Click prediction for product search on C2C web sites
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Predictive client-side profiles for personalized advertising
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Relational click prediction for sponsored search
Proceedings of the fifth ACM international conference on Web search and data mining
Statistical techniques for online personalized advertising: a survey
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Multimedia features for click prediction of new ads in display advertising
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
The impact of images on user clicks in product search
Proceedings of the Twelfth International Workshop on Multimedia Data Mining
Demographic context in web search re-ranking
Proceedings of the 21st ACM international conference on Information and knowledge management
Measuring the Visual Complexities of Web Pages
ACM Transactions on the Web (TWEB)
From republicans to teenagers --- group membership and search (GRUMPS)
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Learning to personalize query auto-completion
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Psychological advertising: exploring user psychology for click prediction in sponsored search
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
CTR prediction for contextual advertising: learning-to-rank approach
Proceedings of the Seventh International Workshop on Data Mining for Online Advertising
Predicting user activity level in social networks
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Incorporating user preferences into click models
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Up or Down? Click-Through Rate Prediction from Social Intention for Search Advertising
Proceedings of International Conference on Information Integration and Web-based Applications & Services
Exploiting contextual factors for click modeling in sponsored search
Proceedings of the 7th ACM international conference on Web search and data mining
Sampling dilemma: towards effective data sampling for click prediction in sponsored search
Proceedings of the 7th ACM international conference on Web search and data mining
Estimating ad group performance in sponsored search
Proceedings of the 7th ACM international conference on Web search and data mining
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Sponsored search is a multi-billion dollar business that generates most of the revenue for search engines. Predicting the probability that users click on ads is crucial to sponsored search because the prediction is used to influence ranking, filtering, placement, and pricing of ads. Ad ranking, filtering and placement have a direct impact on the user experience, as users expect the most useful ads to rank high and be placed in a prominent position on the page. Pricing impacts the advertisers' return on their investment and revenue for the search engine. The objective of this paper is to present a framework for the personalization of click models in sponsored search. We develop user-specific and demographic-based features that reflect the click behavior of individuals and groups. The features are based on observations of search and click behaviors of a large number of users of a commercial search engine. We add these features to a baseline non-personalized click model and perform experiments on offline test sets derived from user logs as well as on live traffic. Our results demonstrate that the personalized models significantly improve the accuracy of click prediction.