The significance of the Cranfield tests on index languages
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
Evaluating evaluation measure stability
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
A review of web searching studies and a framework for future research
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science
Evaluation by highly relevant documents
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Why batch and user evaluations do not give the same results
Proceedings of the 24th 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)
A Task-Oriented Non-Interactive Evaluation Methodologyfor Information Retrieval Systems
Information Retrieval
Information Processing and Management: an International Journal
ACM SIGIR Forum
The perfect search engine is not enough: a study of orienteering behavior in directed search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
Retrieval evaluation with incomplete information
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Information retrieval system evaluation: effort, sensitivity, and reliability
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
When will information retrieval be "good enough"?
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
User performance versus precision measures for simple search tasks
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Score standardization for inter-collection comparison of retrieval systems
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
The good and the bad system: does the test collection predict users' effectiveness?
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
How does clickthrough data reflect retrieval quality?
Proceedings of the 17th ACM conference on Information and knowledge management
Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs
Proceedings of the 17th ACM conference on Information and knowledge management
Predicting bounce rates in sponsored search advertisements
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Metric and Relevance Mismatch in Retrieval Evaluation
AIRS '09 Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
Beyond DCG: user behavior as a predictor of a successful search
Proceedings of the third ACM international conference on Web search and data mining
ACM Transactions on Information Systems (TOIS)
Co-optimization of multiple relevance metrics in web search
Proceedings of the 19th international conference on World wide web
A review of factors influencing user satisfaction in information retrieval
Journal of the American Society for Information Science and Technology
Predicting searcher frustration
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Comparing the sensitivity of information retrieval metrics
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Evaluating search engines by clickthrough data
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part II
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
Find it if you can: a game for modeling different types of web search success using interaction data
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Predicting web searcher satisfaction with existing community-based answers
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Proceedings of the 20th ACM international conference on Information and knowledge management
Large-scale validation and analysis of interleaved search evaluation
ACM Transactions on Information Systems (TOIS)
A semi-supervised approach to modeling web search satisfaction
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Social annotations: utility and prediction modeling
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
When web search fails, searchers become askers: understanding the transition
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Deriving query intents from web search engine queries
Journal of the American Society for Information Science and Technology
Assessing the relationship between context, user preferences, and content in search behaviour
Proceedings of the 5th Ph.D. workshop on Information and knowledge
Models and metrics: IR evaluation as a user process
Proceedings of the Seventeenth Australasian Document Computing Symposium
Differences in search engine evaluations between query owners and non-owners
Proceedings of the sixth ACM international conference on Web search and data mining
Playing by the rules: mining query associations to predict search performance
Proceedings of the sixth ACM international conference on Web search and data mining
Epistemology, pedagogy, assessment and learning analytics
Proceedings of the Third International Conference on Learning Analytics and Knowledge
Toward self-correcting search engines: using underperforming queries to improve search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Click model-based information retrieval metrics
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Personalized models of search satisfaction
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Beyond clicks: query reformulation as a predictor of search satisfaction
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Users versus models: what observation tells us about effectiveness metrics
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Choices in batch information retrieval evaluation
Proceedings of the 18th Australasian Document Computing Symposium
Modeling dwell time to predict click-level satisfaction
Proceedings of the 7th ACM international conference on Web search and data mining
Struggling or exploring?: disambiguating long search sessions
Proceedings of the 7th ACM international conference on Web search and data mining
Evaluation in Music Information Retrieval
Journal of Intelligent Information Systems
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Per-query relevance measures provide standardized, repeatable measurements of search result quality, but they ignore much of what users actually experience in a full search session. This paper examines how well we can approximate a user's ultimate session-level satisfaction using a simple relevance metric. We find that thisrelationship is surprisingly strong. By incorporating additional properties of the query itself, we construct a model which predicts user satisfaction even more accurately than relevance alone.