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|Title:||Keyword-aware optimal location query in road network|
|Citation:||Lecture Notes in Artificial Intelligence, 2016 / Cui, B., Zhang, N., Xu, J., Lian, X., Liu, D. (ed./s), vol.9658, pp.164-177|
|Series/Report no.:||Lecture Notes in Computer Science|
|Conference Name:||International Conference on Web-Age Information Management (WAIM) (3 Jun 2016 - 5 Jun 2016 : Nanchang, China)|
|Jinling Bao, B, Xingshan Liu, Rui Zhou, and Bin Wang|
|Abstract:||In this paper, we study a very useful type of optimal location query, motivated by the following real application: for property renting or purchasing, a client often wants to find a residence such that the sum of the distances between this residence and its nearest facilities is minimal, and meanwhile the residence should be on one of the client-selected road segments (representing where the client prefers to live). The facilities are categorized with keywords, eg., school, hospital and supermarket, and in this problem one facility for each category is required. To the best of our knowledge, this type of query has not been studied before. To tackle this problem, we propose a basic algorithm based on dividing roads (edges) into sub-intervals and find the optimal locations by only inspecting the endpoints of the sub-intervals. We also propose an improved algorithm with keyword filtering and edge pruning strategies. Finally, we demonstrate the efficiency of our algorithms with extensive experiments on large-scale real datasets.|
|Keywords:||Optimal location query; Keyword-aware; In Road network|
|Rights:||© Springer International Publishing Switzerland 2016|
|Appears in Collections:||Aurora harvest 3|
Computer Science publications
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