Scientists at Microsoft Corp. are developing new techniques for analyzing search click-through patterns and browsing behaviors to make search results more relevant. Microsoft researchers Eugene Agichtein, Eric Brill, Susan Dumais and Robert Ragno report that accurate modeling and interpretation of user interactions with a search engine can significantly improve search-result ranking, the detection of �click-spam,� Web search personalization and, ultimately, the overall Web search experience. While user interactions with the Web search engines are plentiful, new robust techniques are required to understand the relationship between user interactions and result quality.

The paper detailing this research, �Learning User Interaction Models for Predicting Web Search Result Preferences,� represents one of 13 papers to be presented by Microsoft Research at the 29th annual ACM SIGIR (Association for Computing Machinery�s Special Interest Group on Information Retrieval) conference on search and information retrieval in Seattle this week. Microsoft Research contributed the largest number of papers to this year�s conference, presenting 17.5 percent of the 74 papers accepted out of a record 399 submissions. SIGIR is a top international forum for the presentation of new research results and the demonstration of new systems and techniques in the broad field of information retrieval.