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- Sha Hu
- Renmin University of China, Beijing, China
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- Zhicheng Dou
- Renmin University of China, Beijing, China
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- Xiaojie Wang
- Renmin University of China, Beijing, China
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- Tetsuya Sakai
- Waseda University, Tokyo, Japan
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- Ji-Rong Wen
- Renmin University of China, Beijing, China
書誌事項
- 公開日
- 2015-10-17
- 権利情報
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- https://www.acm.org/publications/policies/copyright_policy#Background
- DOI
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- 10.1145/2806416.2806455
- 公開者
- ACM
説明
A large percentage of queries issued to search engines are broad or ambiguous. Search result diversification aims to solve this problem, by returning diverse results that can fulfill as many different information needs as possible. Most existing intent-aware search result diversification algorithms formulate user intents for a query as a flat list of subtopics. In this paper, we introduce a new hierarchical structure to represent user intents and propose two general hierarchical diversification models to leverage hierarchical intents. Experimental results show that our hierarchical diversification models outperform state-of-the-art diversification methods that use traditional flat subtopics.
収録刊行物
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- Proceedings of the 24th ACM International on Conference on Information and Knowledge Management
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Proceedings of the 24th ACM International on Conference on Information and Knowledge Management 63-72, 2015-10-17
ACM