| dc.contributor | 資訊管理系 | zh_Tw |
| dc.creator (作者) | 陳良弼 | zh_TW |
| dc.creator (作者) | Jheng, Ruei Sian | en_US |
| dc.creator (作者) | Wang, En Tzu | en_US |
| dc.creator (作者) | Chen, Arbee L. P. | en_US |
| dc.date (日期) | 2015 | en_US |
| dc.date.accessioned | 14-Aug-2017 15:34:13 (UTC+8) | - |
| dc.date.available | 14-Aug-2017 15:34:13 (UTC+8) | - |
| dc.date.issued (上傳時間) | 14-Aug-2017 15:34:13 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/111935 | - |
| dc.description.abstract (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. | en_US |
| dc.format.extent | 2559357 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | DATA 2015 - 4th International Conference on Data Management Technologies and Applications, Proceedings, (), 101-110 | en_US |
| dc.subject (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) | en_US |
| dc.title (題名) | Determining top-k candidates by reverse constrained skyline queries | en_US |
| dc.type (資料類型) | conference | |
