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机构地区:[1]School of Information, Renmin University of China, Beijing 100872, China [2]Key Laboratory of Data Engineering and Knowledge Engineering, Ministry of Education, Beijing 100872, China
出 处:《Journal of Computer Science & Technology》2015年第4期888-901,共14页计算机科学技术学报(英文版)
摘 要:In search engines, different users may search for different information by issuing the same query. To satisfy more users with limited search results, search result diversification re-ranks the results to cover as many user intents as possible. Most existing intent-aware diversification algorithms recognize user intents as subtopics, each of which is usually a word, a phrase, or a piece of description. In this paper, we leverage query facets to understand user intents in diversification, where each facet contains a group of words or phrases that explain an underlying intent of a query. We generate subtopics based on query facets and propose faceted diversification approaches. Experimental results on the public TREC 2009 dataset show that our faceted approaches outperform state-of-the-art diversification models.In search engines, different users may search for different information by issuing the same query. To satisfy more users with limited search results, search result diversification re-ranks the results to cover as many user intents as possible. Most existing intent-aware diversification algorithms recognize user intents as subtopics, each of which is usually a word, a phrase, or a piece of description. In this paper, we leverage query facets to understand user intents in diversification, where each facet contains a group of words or phrases that explain an underlying intent of a query. We generate subtopics based on query facets and propose faceted diversification approaches. Experimental results on the public TREC 2009 dataset show that our faceted approaches outperform state-of-the-art diversification models.
关 键 词:query intent query facet search result diversification
分 类 号:TP393.4[自动化与计算机技术—计算机应用技术] TP311.13[自动化与计算机技术—计算机科学与技术]
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