Top-k Spatial Preference Query for Group Nearest Neighbor
Mo Chen · Journal of Northeastern University · 2015
Spatial preference query is a popular focus of the current research on spatial queries.How ever,the present spatial preference queries cannot be used in the location-based services for group users. To solve this problem,a novel type of spatial preference query,namely,Top-k spatial preference query for group nearest neighbor( TSPG) was proposed,which retrieves the kλ-subsets with the highest score through finding λ-subsets group nearest neighbors of the feature objects. Two algorithms,namely,TSPQ-G and TSPQ-G*were designed for efficient query processing. Based on the TSPQ-G,the TSPQ-G*was developed by performing spatial pruning strategies and efficient traversal strategies of feature objects index,which effectively reduces I / O cost and improves query efficiency. Experimental results on several datasets demonstrated the effectiveness of the proposed algorithms for different setups.