Information filtering based on user behavior analysis and best match text retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
A case for interaction: a study of interactive information retrieval behavior and effectiveness
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The cluster hypothesis revisited
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Grouper: a dynamic clustering interface to Web search results
WWW '99 Proceedings of the eighth international conference on World Wide Web
A 3D Based User Interface for Information Retrieval Systems
Proceedings of the IEEE Visualization '93 Workshop on Database Issues for Data Visualization
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Re-examining the potential effectiveness of interactive query expansion
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Dynamic Programming
Negative pseudo-relevance feedback in content-based video retrieval
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
Questioning query expansion: an examination of behaviour and parameters
ADC '04 Proceedings of the 15th Australasian database conference - Volume 27
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
Context-sensitive information retrieval using implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Active feedback in ad hoc information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Implicit user modeling for personalized search
Proceedings of the 14th ACM international conference on Information and knowledge management
A study of interface support mechanisms for interactive information retrieval
Journal of the American Society for Information Science and Technology - Research Articles
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
Less is more: probabilistic models for retrieving fewer relevant documents
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Multi-armed bandit problems with dependent arms
Proceedings of the 24th international conference on Machine learning
An experimental comparison of click position-bias models
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Learning diverse rankings with multi-armed bandits
Proceedings of the 25th international conference on Machine learning
Selecting good expansion terms for pseudo-relevance feedback
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Novelty and diversity in information retrieval evaluation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Active relevance feedback for difficult queries
Proceedings of the 17th ACM conference on Information and knowledge management
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Classifying and Characterizing Query Intent
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Portfolio theory of information retrieval
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
The Probabilistic Relevance Framework: BM25 and Beyond
Foundations and Trends in Information Retrieval
Inferring query intent from reformulations and clicks
Proceedings of the 19th international conference on World wide web
On statistical analysis and optimization of information retrieval effectiveness metrics
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Interactive retrieval based on faceted feedback
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the fourth ACM international conference on Web search and data mining
Balancing exploration and exploitation in learning to rank online
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Structured learning of two-level dynamic rankings
Proceedings of the 20th ACM international conference on Information and knowledge management
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
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Modern information retrieval interfaces typically involve multiple pages of search results, and users who are recall minded or engaging in exploratory search using ad hoc queries are likely to access more than one page. Document rankings for such queries can be improved by allowing additional context to the query to be provided by the user herself using explicit ratings or implicit actions such as clickthroughs. Existing methods using this information usually involved detrimental UI changes that can lower user satisfaction. Instead, we propose a new feedback scheme that makes use of existing UIs and does not alter user's browsing behaviour; to maximise retrieval performance over multiple result pages, we propose a novel retrieval optimisation framework and show that the optimal ranking policy should choose a diverse, exploratory ranking to display on the first page. Then, a personalised re-ranking of the next pages can be generated based on the user's feedback from the first page. We show that document correlations used in result diversification have a significant impact on relevance feedback and its effectiveness over a search session. TREC evaluations demonstrate that our optimal rank strategy (including approximative Monte Carlo Sampling) can naturally optimise the trade-off between exploration and exploitation and maximise the overall user's satisfaction over time against a number of similar baselines.