The vocabulary problem in human-system communication
Communications of the ACM
Automatic text processing
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
The effect of adding relevance information in a relevance feedback environment
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Pivoted document length normalization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Helping people find what they don't know
Communications of the ACM
Proceedings of the 6th international conference on Intelligent user interfaces
A vector space model for automatic indexing
Communications of the ACM
The Importance of Prior Probabilities for Entry Page Search
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Finding relevant documents using top ranking sentences: an evaluation of two alternative schemes
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Vector space model of information retrieval: a reevaluation
SIGIR '84 Proceedings of the 7th annual international ACM SIGIR conference on Research and development in information retrieval
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
The Geometry of Information Retrieval
The Geometry of Information Retrieval
Understanding implicit feedback and document preference: a naturalistic user study
Understanding implicit feedback and document preference: a naturalistic user study
Display time as implicit feedback: understanding task effects
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
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
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
The Turn: Integration of Information Seeking and Retrieval in Context (The Information Retrieval Series)
Context modeling and discovery using vector space bases
Proceedings of the 14th ACM international conference on Information and knowledge management
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
A study on the effects of personalization and task information on implicit feedback performance
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Ranking in context using vector spaces
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Studying the use of popular destinations to enhance web search interaction
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
The lumière project: Bayesian user modeling for inferring the goals and needs of software users
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
A basis for information retrieval in context
ACM Transactions on Information Systems (TOIS)
Automatically Maintained Domain Knowledge: Initial Findings
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Toward the design of a methodology to predict relevance through multiple sources of evidence
PIKM '10 Proceedings of the 3rd workshop on Ph.D. students in information and knowledge management
Combining interaction and content for feedback-based ranking
IRFC'11 Proceedings of the Second international conference on Multidisciplinary information retrieval facility
Modeling the evolution of context in information retrieval
FDIA'08 Proceedings of the 2nd BCS IRSG conference on Future Directions in Information Access
Automatically adapting the context of an intranet query
FDIA'08 Proceedings of the 2nd BCS IRSG conference on Future Directions in Information Access
Re-ranking with context for high-performance biomedical information retrieval
International Journal of Data Mining and Bioinformatics
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Implicit feedback algorithms utilize interaction between searchers and search systems to learn more about users' needs and interests than expressed in query statements alone. This additional information can be used to formulate improved queries or directly improve retrieval performance. In this paper we present a geometric framework that utilizes multiple sources of evidence present in this interaction context (e.g., display time, document retention) to develop enhanced implicit feedback models personalized for each user and tailored for each search task. We use rich interaction logs (and associated metadata such as relevance judgments), gathered during a longitudinal user study, as relevance stimuli to compare an implicit feedback algorithm developed using the framework with alternative algorithms. Our findings demonstrate both the effectiveness of our proposed algorithm and the potential value of incorporating multiple sources of interaction evidence when developing implicit feedback algorithms.