ACM SIGIR Forum
Query type classification for web document retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
Automatic identification of user goals in Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Accurately interpreting clickthrough data as implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
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Web users usually have a certain search goal before they submit a search query. However, many laypersons can't transform their search goals into suitable queries. Thus, understanding original search goals behind a query is very important for search engines. In the past decade, many researches focus on classifying search goals behind a query into different search-goal categories. In fact, there may be more than one search goal behind a certain query. We thus propose a novel Popular-Search-Goal-based Search Model to effectively identify search goals by the features extracted from search-result snippets and click-through data. Furthermore, we proposed a Search-Goal-based Ranking Model which exploits the identified search goals to re-rank the search result. The experimental result shows our proposed model can effectively identify the search goals behind a search query (achieve precision of 0.94) and enhance the search result ranking (achieve precision of 0.72 for top-1 returned snippet).