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https://ah.lib.nccu.edu.tw/handle/140.119/111935
題名: | Determining top-k candidates by reverse constrained skyline queries | 作者: | 陳良弼 Jheng, Ruei Sian Wang, En Tzu Chen, Arbee L. P. |
貢獻者: | 資訊管理系 | 關鍵詞: | 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 | 上傳時間: | 14-Aug-2017 | 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 | 資料類型: | conference |
Appears in Collections: | 會議論文 |
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DATA_2015_17.pdf | 2.5 MB | Adobe PDF2 | View/Open |
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