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政大機構典藏 > 商學院 > 資訊管理學系 > 會議論文 > Item 140.119/111935

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题名:	Determining top-k candidates by reverse constrained skyline queries
作者:	陳良弼 Jheng, Ruei Sian Wang, En Tzu Chen, Arbee L. P.
贡献者:	資訊管理系
关键词:	Decision trees;Information management;Query processing;Object o;Potential customers;Pruning strategy;Quad trees;Range query;Skyline query;Straight-forward method;Top-k query;Indexing (of information)
日期:	2015
上传时间:	2017-08-14 15:34:13 (UTC+8)
摘要:	Given a set of criteria, an object o is defined to dominate another object o` if o is no worse than o` in each criterion and has better outcomes in at least a specific criterion. A skyline query returns each object that is not dominated by any other objects. Consider a scenario as follows. Given three types of datasets, including residents in a city, existing restaurants in the city, and candidate places for opening new restaurants in the city, where each restaurant and candidate place has its respective rank on a set of criteria, e.g., convenience of parking, we want to find the top-k candidate places that have the most potential customers. The potential customers of a candidate place is defined as the number of residents whose distance to this candidate is no larger than a given distance r and also regard this candidate as their skyline restaurants. In this paper, we propose an efficient method based on the quad-tree index and use four pruning strategies to solve this problem. A series of experiments are performed to compare the proposed method with a straightforward method using the R-tree index. The experiment results demonstrate that the proposed method is very efficient, and the pruning strategies very powerful.
關聯:	DATA 2015 - 4th International Conference on Data Management Technologies and Applications, Proceedings, (), 101-110
数据类型:	conference
显示于类别:	[資訊管理學系] 會議論文

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