Techniques for automatically correcting words in text
ACM Computing Surveys (CSUR)
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
The Wisdom of Crowds
Improving personalized web search using result diversification
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
What are you looking for?: an eye-tracking study of information usage in web search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Exploring mouse movements for inferring query intent
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Survey and evaluation of query intent detection methods
Proceedings of the 2009 workshop on Web Search Click Data
Explore/Exploit Schemes for Web Content Optimization
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
Anatomy of the long tail: ordinary people with extraordinary tastes
Proceedings of the third ACM international conference on Web search and data mining
Modern Information Retrieval
Predicting searcher frustration
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
User browsing models: relevance versus examination
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
No clicks, no problem: using cursor movements to understand and improve search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The Filter Bubble: What the Internet Is Hiding from You
The Filter Bubble: What the Internet Is Hiding from You
Proceedings of the 22nd international conference on World Wide Web companion
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Web Search, which takes its root in the mature field of information retrieval, evolved tremendously over the last 20 years. The field encountered its first revolution when it started to deal with huge amounts of Web pages. Then, a major step was accomplished when engines started to consider the structure of the Web graph and link analysis became a differentiator in both crawling and ranking. Finally, a more discrete, but not less critical step, was made when search engines started to monitor and mine the numerous (mostly implicit) signals provided by users while interacting with the search engine. We focus here on this third "revolution" of large scale usage data. We detail the different shapes it takes, illustrating its benefits through a review of some winning search features that could not have been possible without it. We also discuss its limitations and how in some cases it even conflicts with some natural users' aspirations such as personalization and privacy. We conclude by discussing how some of these conflicts can be circumvented by using adequate aggregation principles to create "ad hoc"crowds.