automatic identification of user goals in web search
There has been recent interests in studying the "goal" behind a user's Web query, so that this goal can be used to improve the quality of a search engine's results. Previous studies have mainly focused on using manual query-log investigation to identify Web query goals. In this paper we study whether and how we can automate this goal-identification process. We first present our results from a human subject study that strongly indicate the feasibility of automatic query-goal identification. We then propose two types of features for the goal-identification task: user-click behavior and anchor-link distribution . Our experimental evaluation shows that by combining these features we can correctly identify the goals for 90\% of the queries studied.
automation identification user user goals goals web search web queries queries quality search engine paper process human types feature task experimental evaluation combinational linking query log query classification query