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  • 标题:Efficiently Detecting the Top Nearest Neighbor Objects in Spatial Database
  • 本地全文:下载
  • 作者:Kumar Vasantha ; Dhana Krishna. K
  • 期刊名称:International Journal of Computer Science & Technology
  • 印刷版ISSN:2229-4333
  • 电子版ISSN:0976-8491
  • 出版年度:2012
  • 卷号:3
  • 期号:4
  • 页码:567-572
  • 语种:English
  • 出版社:Ayushmaan Technologies
  • 摘要:Spatial database systems manage large collections of geographic entities, which apart from spatial attributes contain spatial information and non spatial information. An attractive type of preference queries, which select the best spatial location with respect to the quality of facilities in its spatial area. User preference queries are very important in spatial databases. With the help of these queries, one can found best location among points saved in database. In many situation users evaluate quality of a location with its distance from its nearest neighbor among a special set of points There has been less attention about evaluating a location with its distance to nearest neighbors in spatial user preference queries. This problem has application in many domains such as service recommendation systems and investment planning. Related works in this field are based on top-k queries. The problem with top-k queries is that user must set weights for attributes nd a function for aggregating them. This is hard for him in most cases. In this paper a new type of user preference queries called spatial nearest neighbor skyline queries will be introduced in which user has some sets of points as query parameters. For each point in database attributes are its distances to the nearest neighbors from each set of query points. By separating this query as a subset of dynamic skyline queries N2S2 algorithm is provided for computing it. This algorithm has good performance compared with the general branch and bound algorithm for skyline queries.
  • 关键词:User Preference Queries;Nearest Neighbor;Skyline Queries; Spatial Databases
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