Abstract: Spatial preference query is a popular focus of the current research on spatial queries. However， 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 k λ-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.

Key words: spatial preference, location-based service, group nearest neighbor, pruning, query