Skyline Minimum Vector
Skyline Minimum Vector
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DOI：
10.1109/apweb.2010.34
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发表时间：
2010-04
期刊：
影响因子：
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通讯作者：
S. Jang;C. Park;Jaesoo Yoo
中科院分区：
文献类型：
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作者：
S. Jang;C. Park;Jaesoo Yoo
天际线查询通常用于多种推荐应用程序中。大多数现有相关工作都集中在许多多维数据中的天际线计算上。但是，这些作品并未考虑从非阳性点产生的有趣查询。在本文中，我们提出了一个新的查询，称为Skyline最低矢量，该查询找到了将非阳性点提高到天际线的最小向量。天际线最小矢量意味着成为天际线的最低成本。我们使用天际线和查询点之间的曼哈顿距离来评估成本。此外，我们提出了基本算法和优化算法，以获取天际线最小值。拟议的查询将在许多决策应用中非常有用。
The skyline queries are often used in several recommendation applications. Most existing related works have focused on skyline computation in many multidimensional data. However, these works do not consider an interesting query generated from non-skyline point. In this paper, we propose a new query, called skyline minimum vector which finds the minimum vector for making a non-skyline point into a skyline. The skyline minimum vector means the minimum cost for becoming a skyline. We use the Manhattan distance between skyline and query point in order to evaluate the cost. Also, we propose basic algorithm and optimized algorithm for getting skyline minimum vector. The proposed query will be very useful in many decision-making applications.