Subject-oriented top-k hot region queries in spatial dataset

  • Authors:
  • Junling Liu;Ge Yu;Huanliang Sun

  • Affiliations:
  • Northeastern University, Shenyang Jianzhu University, Shenyang, China;Northeastern University, Shenyang, China;Shenyang Jianzhu University, Shenyang, China

  • Venue:
  • Proceedings of the 20th ACM international conference on Information and knowledge management
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper proposes and solves a novel type of spatial queries named Subject-oriented Top-k hot Region (STR) queries. Given a subject S defined by a feature set R and features importance denoted by weights, an STR query retrieves k non-overlapping regions that have the highest scores computed by the number of feature objects and their weights. As an example, the culture subject is defined by exhibition halls, libraries and museums. On the subject, an STR query finds cultural centers intensively distributed feature objects. In this paper, we propose two efficient algorithms, single-partition (SP) algorithm and dual-partition (DP) algorithm, to process STR queries. Extensive experiments evaluate the proposed solutions under a wide range of parameter settings.