Combining top-k query in road networks

  • Authors:

  • Weimo Liu;Yinan Jing;Kunjie Chen;Weiwei Sun

  • Affiliations:

  • School of Computer Science, Fudan University, Shanghai, China;School of Computer Science, Fudan University, Shanghai, China;School of Computer Science, Fudan University, Shanghai, China;School of Computer Science, Fudan University, Shanghai, China

  • Venue:
  • WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
  • Year:
  • 2011

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Abstract

In location-based services, every query object usually has multiple attributes including its location in road networks. However, when making a decision to choose an object, there is probably no such an object that is best in every attribute. To have a balance among all the attributes, a monotone aggregation function can be used, in which every attribute is an independent variable of the function. To find k objects which have the minimal (maximal) values of the function is a typical combining top-k problem. In this paper, we address this problem in road network environment. To answer such a query more efficiently, we propose a novel algorithm called ATC (Access with Topology Changed). By making use of road networks' locality, the algorithm changes the networks' topology and reduces the number of data access. Extensive experiments show that our algorithm can obviously outperform existing algorithms that solve the combining top-k problem.