Communications of the ACM
Beyond independent relevance: methods and evaluation metrics for subtopic retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Personalized Web Search For Improving Retrieval Effectiveness
IEEE Transactions on Knowledge and Data Engineering
Ontology-based personalized search and browsing
Web Intelligence and Agent Systems
Context-sensitive information retrieval using implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Using ODP metadata to personalize search
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Personalizing search via automated analysis of interests and activities
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Personalized Search Based on User Search Histories
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Mining long-term search history to improve search accuracy
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Investigating behavioral variability in web search
Proceedings of the 16th international conference on World Wide Web
A large-scale evaluation and analysis of personalized search strategies
Proceedings of the 16th international conference on World Wide Web
Random walks on the click graph
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
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
Context-aware query suggestion by mining click-through and session data
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
PSkip: estimating relevance ranking quality from web search clickthrough data
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Context-aware query classification
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Smoothing clickthrough data for web search ranking
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
ACM Transactions on Computer-Human Interaction (TOCHI)
Classification-enhanced ranking
Proceedings of the 19th international conference on World wide web
Predicting short-term interests using activity-based search context
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Personalizing web search using long term browsing history
Proceedings of the fourth ACM international conference on Web search and data mining
Modeling the impact of short- and long-term behavior on search personalization
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Search, interrupted: understanding and predicting search task continuation
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Beliefs and biases in web search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Personalized ranking model adaptation for web search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Search engine switching detection based on user personal preferences and behavior patterns
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Query change as relevance feedback in session search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Search result presentation: supporting post-search navigation by integration of taxonomy data
Proceedings of the 22nd international conference on World Wide Web companion
Know your personalization: learning topic level personalization in online services
Proceedings of the 22nd international conference on World Wide Web
Enhancing personalized search by mining and modeling task behavior
Proceedings of the 22nd international conference on World Wide Web
Intent models for contextualising and diversifying query suggestions
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Personalization of web-search using short-term browsing context
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Take this personally: pollution attacks on personalized services
SEC'13 Proceedings of the 22nd USENIX conference on Security
Multimedia search reranking: A literature survey
ACM Computing Surveys (CSUR)
Adapting deep RankNet for personalized search
Proceedings of the 7th ACM international conference on Web search and data mining
User modeling in search logs via a nonparametric bayesian approach
Proceedings of the 7th ACM international conference on Web search and data mining
From devices to people: attribution of search activity in multi-user settings
Proceedings of the 23rd international conference on World wide web
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We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms using either direct human relevance judgments or indirect judgments obtained from click-through data from millions of users. The rankings are thus optimized to this generic population of users, not to any specific user. We propose a generative model of relevance which can be used to infer the relevance of a document to a specific user for a search query. The user-specific parameters of this generative model constitute a compact user profile. We show how to learn these profiles from a user's long-term search history. Our algorithm for computing the personalized ranking is simple and has little computational overhead. We evaluate our personalization approach using historical search data from thousands of users of a major Web search engine. Our findings demonstrate gains in retrieval performance for queries with high ambiguity, with particularly large improvements for acronym queries.