New techniques for analyzing search relevance--the way users browse and click through specific content--can improve the algorithms used to rank results, according to two papers submitted by a group of Microsoft researchers.
"Most search engines today use a somewhat two-dimensional approach, matching user queries with the content and link structure of Web pages to return a list of results. We're looking at how to add a third dimension--the users themselves--to improve the search experience," said Eugene Agichtein, a researcher in the Mining, Search and Navigation Group within Microsoft Research.
Thirteen Microsoft papers--10 of them collaborations with university researchers--will be presented at the 29th Annual International Association for Computing Machinery's Special Interest Group on Information Retrieval (ACM SIGIR 2006), which started on Sunday and continues through Aug. 11 in Seattle.
One of the papers, "Learning User Interaction Models for Predicting Web Search Results Preferences," illustrates new techniques for following users beyond the first click-through from a search results page.
The researchers applied factors such as the amount of time spent "dwelling" on a given page, the page with the most "dwell time" for a user given the user's average dwell time per page, and dwell time for pages that rank high for sharing search words with their domain. The researchers looked at the fraction of words shared between search terms, and the domain names, page titles or summaries clicked on by the searcher.
"Using the 'wisdom of crowds' can give us an accurate interpretation of user interactions, even in the inherently noisy Web search setting. Our techniques allow us to automatically predict relevance preferences for Web search results with accuracy greater than the previously published methods," the Microsoft research group said in its paper.
A second paper presented by the same group of researchers discusses how to apply that user information to improve search algorithms. The researchers used an evaluation of 3,000 searches and 12 million user interactions to show that they could improve Web-search-ranking algorithms by 31 percent with their methods.
Other ACM SIGIR search topics focus on translating large amounts of content into smaller, digestible forms. A paper to be presented by researchers from Microsoft, Stanford University and Columbia University covers a "composition context sensitive" system for summarizing multiple documents. A team from the University of Cyprus and the University of Michigan is slated to discuss presenting text summarizations of news stories in formats better suited for mobile devices.
Worldwide, Microsoft's Web browser, Firefox Internet browser. Microsoft, whose search engine is MSN Search, recently teamed up with search competitors such as ., has a usage rate of 83.05 percent, according to the Web analytics company OneStat.com. at 12.93 percent. Search giant Google, , has paired with Mozilla on its