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    政大機構典藏 > 理學院 > 資訊科學系 > 會議論文 >  Item 140.119/75791
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/75791


    Title: On continuous spatial skyline queries over a line segment
    Authors: Tai, W.H.;Wang, E.T.;Chen, Arbee L. P.
    陳良弼
    Contributors: 資科系
    Keywords: Beaches;Constraint satisfaction problems;Experiments;Expert systems;Indexing (of information);Distance constraints;Dynamic attributes;Line segment;Location constraints;Location data;Similarity functions;Skyline;Two dimensional spaces;Query processing
    Date: 2014-09
    Issue Date: 2015-06-15 16:05:25 (UTC+8)
    Abstract: Traditional skyline queries consider data points with static attributes, e.g., the distance to a beach of a hotel. However, some attributes considered for a skyline query can be dynamic, e.g., the distance to a beach of a moving vehicle. Consider a scenario as follows. A person in a moving vehicle issues a skyline query to find restaurants, taking into account the static attributes of the restaurants as well as the distance to them. This scenario motives us to address a novel skyline query considering both static and dynamic attributes of data points. Given a data set D (e.g., restaurants) with a set of static attributes in a two-dimensional space, a query line segment l (e.g., the route for driving), and a distance constraint of r (for choosing a restaurant), we want to find out the skylines along l considering the static and dynamic attributes of the data points, satisfying the location constraint of r. We propose two methods to solve the problem. In the first method, we find some special location points which partition l into sub-segments and also make the skylines in the adjacent sub-segments different. In the second method, we apply some properties to identify data points which need not be considered for computing skylines. Moreover, to reduce the number of sub-segments, we propose an approximate method to compute skylines and define a similarity function to measure the similarity between the exact and approximate results. A series of experiments are performed to evaluate the exact methods and the results show that the second method is more efficient. We also perform experiments to compare the exact and approximate results and it shows that there is a trade-off between the reduction of the number of sub-segments and the accuracy of the results. © 2014 Springer International Publishing Switzerland.
    Relation: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 8644 LNCS, Issue PART 1, 2014, Pages 171-187, 25th International Conference on Database and Expert Systems Applications, DEXA 2014; Munich; Germany; 1 September 2014 到 4 September 2014; 代碼 107150
    Data Type: conference
    DOI 連結: http://dx.doi.org/10.1007/978-3-319-10073-9-14
    DOI: 10.1007/978-3-319-10073-9-14
    Appears in Collections:[資訊科學系] 會議論文

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