Real life, real users, and real needs: a study and analysis of user queries on the web
Information Processing and Management: an International Journal
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Hourly analysis of a very large topically categorized web query log
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Detecting online commercial intention (OCI)
Proceedings of the 15th international conference on World Wide Web
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
Investigating the querying and browsing behavior of advanced search engine users
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
How well does result relevance predict session satisfaction?
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
The relationship between IR effectiveness measures and user satisfaction
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
User adaptation: good results from poor systems
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
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Predicting query reformulation during web searching
CHI '09 Extended Abstracts on Human Factors in Computing Systems
Evaluating web search using task completion time
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Page hunt: improving search engines using human computation games
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Explaining User Performance in Information Retrieval: Challenges to IR Evaluation
ICTIR '09 Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory
Methods for Evaluating Interactive Information Retrieval Systems with Users
Foundations and Trends in Information Retrieval
Analyzing and evaluating query reformulation strategies in web search logs
Proceedings of the 18th ACM conference on Information and knowledge management
How are we searching the World Wide Web? A comparison of nine search engine transaction logs
Information Processing and Management: an International Journal - Special issue: Formal methods for information retrieval
A model to estimate intrinsic document relevance from the clickthrough logs of a web search engine
Proceedings of the third ACM international conference on Web search and data mining
Beyond DCG: user behavior as a predictor of a successful search
Proceedings of the third ACM international conference on Web search and data mining
How does search behavior change as search becomes more difficult?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Web search engine metrics: (direct metrics to measure user satisfaction)
Proceedings of the 19th international conference on World wide web
Predicting searcher frustration
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Do user preferences and evaluation measures line up?
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Helping identify when users find useful documents: examination of query reformulation intervals
Proceedings of the third symposium on Information interaction in context
Predicting short-term interests using activity-based search context
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Proceedings of the 21st international conference on World Wide Web
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
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
When big data leads to lost data
Proceedings of the 5th Ph.D. workshop on Information and knowledge
Exploring and predicting search task difficulty
Proceedings of the 21st ACM international conference on Information and knowledge management
Predicting web search success with fine-grained interaction data
Proceedings of the 21st ACM international conference on Information and knowledge management
Session-based query performance prediction
Proceedings of the 21st ACM international conference on Information and knowledge management
Playing by the rules: mining query associations to predict search performance
Proceedings of the sixth ACM international conference on Web search and data mining
Personalizing atypical web search sessions
Proceedings of the sixth ACM international conference on Web search and data mining
Intent-Based browse activity segmentation
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Recommending high utility query via session-flow graph
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
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
Improving search result summaries by using searcher behavior data
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Search engine switching detection based on user personal preferences and behavior patterns
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Personalization of web-search using short-term browsing context
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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
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
The last click: why users give up information network navigation
Proceedings of the 7th ACM international conference on Web search and data mining
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A better understanding of strategies and behavior of successful searchers is crucial for improving the experience of all searchers. However, research of search behavior has been struggling with the tension between the relatively small-scale, but controlled lab studies, and the large-scale log-based studies where the searcher intent and many other important factors have to be inferred. We present our solution for performing controlled, yet realistic, scalable, and reproducible studies of searcher behavior. We focus on difficult informational tasks, which tend to frustrate many users of the current web search technology. First, we propose a principled formalization of different types of "success" for informational search, which encapsulate and sharpen previously proposed models. Second, we present a scalable game-like infrastructure for crowdsourcing search behavior studies, specifically targeted towards capturing and evaluating successful search strategies on informational tasks with known intent. Third, we report our analysis of search success using these data, which confirm and extends previous findings. Finally, we demonstrate that our model can predict search success more effectively than the existing state-of-the-art methods, on both our data and on a different set of log data collected from regular search engine sessions. Together, our search success models, the data collection infrastructure, and the associated behavior analysis techniques, significantly advance the study of success in web search.