Long-Term Learning for Web Search Engines
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
An Efficient Boosting Algorithm for Combining Preferences
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Implicit feedback for inferring user preference: a bibliography
ACM SIGIR Forum
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
Evaluating implicit measures to improve web search
ACM Transactions on Information Systems (TOIS)
A study of factors affecting the utility of implicit relevance feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Accurately interpreting clickthrough data as implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
New approaches to support vector ordinal regression
ICML '05 Proceedings of the 22nd international conference on Machine learning
Modeling information navigation: implications for information architecture
Human-Computer Interaction
Journal of Artificial Intelligence Research
Active exploration for learning rankings from clickthrough data
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
An experimental comparison of click position-bias models
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Bypass rates: reducing query abandonment using negative inferences
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
A few bad votes too many?: towards robust ranking in social media
AIRWeb '08 Proceedings of the 4th international workshop on Adversarial information retrieval on the web
Are click-through data adequate for learning web search rankings?
Proceedings of the 17th ACM conference on Information and knowledge management
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Learning consensus opinion: mining data from a labeling game
Proceedings of the 18th international conference on World wide web
Picture this: preferences for image search
Proceedings of the ACM SIGKDD Workshop on Human Computation
Modeling contextual factors of click rates
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Suggesting email view filters for triage and search
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Proceedings of the 19th international conference on World wide web
SpotRank: a robust voting system for social news websites
Proceedings of the 4th workshop on Information credibility
Evaluating search systems using result page context
Proceedings of the third symposium on Information interaction in context
Detecting duplicate web documents using clickthrough data
Proceedings of the fourth ACM international conference on Web search and data mining
Proceedings of the fourth ACM international conference on Web search and data mining
Proceedings of the 20th international conference on World wide web
Large-scale validation and analysis of interleaved search evaluation
ACM Transactions on Information Systems (TOIS)
On caption bias in interleaving experiments
Proceedings of the 21st ACM international conference on Information and knowledge management
Learning to rank for spatiotemporal search
Proceedings of the sixth ACM international conference on Web search and data mining
Bayesian vote weighting in crowdsourcing systems
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
Practical online retrieval evaluation
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Beliefs and biases in web search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Captions and biases in diagnostic search
ACM Transactions on the Web (TWEB)
A unified search federation system based on online user feedback
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
User intent and assessor disagreement in web search evaluation
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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
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Clickthrough data is a particularly inexpensive and plentiful resource to obtain implicit relevance feedback for improving and personalizing search engines. However, it is well known that the probability of a user clicking on a result is strongly biased toward documents presented higher in the result set irrespective of relevance. We introduce a simple method to modify the presentation of search results that provably gives relevance judgments that are unaffected by presentation bias under reasonable assumptions. We validate this property of the training data in interactive real world experiments. Finally, we show that using these unbiased relevance judgments learning methods can be guaranteed to converge to an ideal ranking given sufficient data.