Implicit feedback for inferring user preference: a bibliography
ACM SIGIR Forum
Analysis of internet users' interests based on windows GUI messages
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: applications and services
An overview of Web search evaluation methods
Computers and Electrical Engineering
Interpreting user inactivity on search results
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
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Measuring the information retrieval effectiveness of Web search engines can be expensive if human relevance judgments are required to evaluate search results. Using implicit user feedback for search engine evaluation provides a cost and time effective manner of addressing this problem. Web search engines can use human evaluation of search results without the expense of human evaluators. An additional advantage of this approach is the availability of real time data regarding system performance. Wecapture user relevance judgments actions such as print, save and bookmark, sending these actions and the corresponding document identifiers to a central server via a client application. We use this implicit feedback to calculate performance metrics, such as precision. We can calculate an overall system performance metric based on a collection of weighted metrics.