Optimum polynomial retrieval functions based on the probability ranking principle
ACM Transactions on Information Systems (TOIS)
Making Rational Decisions Using Adaptive Utility Elicitation
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Active Sampling for Class Probability Estimation and Ranking
Machine Learning
Eye-tracking analysis of user behavior in WWW search
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Active learning of label ranking functions
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Shuffling a stacked deck: the case for partially randomized ranking of search engine results
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Learning to rank using gradient descent
ICML '05 Proceedings of the 22nd international conference on Machine learning
Preference learning with Gaussian processes
ICML '05 Proceedings of the 22nd international conference on Machine learning
Learning user interaction models for predicting web search result preferences
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Minimal test collections for retrieval evaluation
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Evaluating the accuracy of implicit feedback from clicks and query reformulations in Web search
ACM Transactions on Information Systems (TOIS)
Minimally invasive randomization for collecting unbiased preferences from clickthrough logs
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Learning diverse rankings with multi-armed bandits
Proceedings of the 25th international conference on Machine learning
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Bypass rates: reducing query abandonment using negative inferences
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Query suggestion using hitting time
Proceedings of the 17th ACM conference on Information and knowledge management
Boosting the ranking function learning process using clustering
Proceedings of the 10th ACM workshop on Web information and data management
Efficient multiple-click models in web search
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Using query logs and click data to create improved document descriptions
Proceedings of the 2009 workshop on Web Search Click Data
Spatio-temporal models for estimating click-through rate
Proceedings of the 18th international conference on World wide web
Active Sampling for Rank Learning via Optimizing the Area under the ROC Curve
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Regret-based online ranking for a growing digital library
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Global ranking by exploiting user clicks
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Good abandonment in mobile and PC internet search
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Entropy-biased models for query representation on the click graph
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Click-through prediction for news queries
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
Learning Preferences with Hidden Common Cause Relations
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Learning to Rank for Information Retrieval
Foundations and Trends in Information Retrieval
Post-rank reordering: resolving preference misalignments between search engines and end users
Proceedings of the 18th ACM conference on Information and knowledge management
Mining search engine clickthrough log for matching N-gram features
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Empirical exploitation of click data for task specific ranking
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Proceedings of the 19th international conference on World wide web
Using clicks as implicit judgments: expectations versus observations
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Investigating the effectiveness of clickthrough data for document reordering
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Mining Query Logs: Turning Search Usage Data into Knowledge
Foundations and Trends in Information Retrieval
The unavailable candidate model: a decision-theoretic view of social choice
Proceedings of the 11th ACM conference on Electronic commerce
Temporal query log profiling to improve web search ranking
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Online learning for recency search ranking using real-time user feedback
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Fast active exploration for link-based preference learning using Gaussian processes
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Using related queries to improve web search results ranking
SPIRE'10 Proceedings of the 17th international conference on String processing and information retrieval
Detecting duplicate web documents using clickthrough data
Proceedings of the fourth ACM international conference on Web search and data mining
Evaluating new search engine configurations with pre-existing judgments and clicks
Proceedings of the 20th international conference on World wide web
Balancing exploration and exploitation in learning to rank online
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Smoothing click counts for aggregated vertical search
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Active learning to maximize accuracy vs. effort in interactive information retrieval
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Efficiently collecting relevance information from clickthroughs for web retrieval system evaluation
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Improving local search ranking through external logs
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Diversity in ranking via resistive graph centers
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 20th ACM international conference on Information and knowledge management
Discovering missing click-through query language information for web search
Proceedings of the 20th ACM international conference on Information and knowledge management
Proceedings of the 20th ACM international conference on Information and knowledge management
ClickRank: Learning Session-Context Models to Enrich Web Search Ranking
ACM Transactions on the Web (TWEB)
Active learning of combinatorial features for interactive optimization
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Enriching query flow graphs with click information
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
An Online Learning Framework for Refining Recency Search Results with User Click Feedback
ACM Transactions on Information Systems (TOIS)
Enriching Documents with Examples: A Corpus Mining Approach
ACM Transactions on Information Systems (TOIS)
A document rating system for preference judgements
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Annotation for free: video tagging by mining user search behavior
Proceedings of the 21st ACM international conference on Multimedia
Incorporating user preferences into click models
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Active evaluation of ranking functions based on graded relevance
Machine Learning
Mining search and browse logs for web search: A Survey
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Active evaluation of ranking functions based on graded relevance (extended abstract)
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Robust ordinal regression in preference learning and ranking
Machine Learning
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We address the task of learning rankings of documents from search enginelogs of user behavior. Previous work on this problem has relied onpassively collected clickthrough data. In contrast, we show that anactive exploration strategy can provide data that leads to much fasterlearning. Specifically, we develop a Bayesian approach for selectingrankings to present users so that interactions result in more informativetraining data. Our results using the TREC-10 Web corpus, as well assynthetic data, demonstrate that a directed exploration strategy quicklyleads to users being presented improved rankings in an online learningsetting. We find that active exploration substantially outperformspassive observation and random exploration.