{"id":161185,"date":"2011-04-20T00:00:00","date_gmt":"2011-04-20T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/a-new-level-of-social-search-discovering-the-users-opinion-before-he-can-make-one\/"},"modified":"2018-10-16T20:11:40","modified_gmt":"2018-10-17T03:11:40","slug":"a-new-level-of-social-search-discovering-the-users-opinion-before-he-can-make-one","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/a-new-level-of-social-search-discovering-the-users-opinion-before-he-can-make-one\/","title":{"rendered":"A new level of social search: discovering the user&#8217;s opinion before he can make one"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Current approaches to social search are generally based on the friends\u2019 opinion and collaborative filtering paradigms, which have limited effectiveness in terms of both accuracy and coverage of the information that may be relevant to a user. We propose a new kind of social search signal, based on the idea of prediction extraction, which is aimed at improving the quality of information available to current methods, as well as introducing new kinds of search methods.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Current approaches to social search are generally based on the friends\u2019 opinion and collaborative filtering paradigms, which have limited effectiveness in terms of both accuracy and coverage of the information that may be relevant to a user. 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