The Flexible Group Spatial Keyword Query

We propose the flexible group spatial keyword query and algorithms to process three variants of the query in the spatial textual domain: (i) the group nearest neighbor with keywords query, which finds the data object that optimizes the aggregate cost function for the whole group Q of size n query objects, (ii) the subgroup nearest neighbor with keywords query, which finds the optimal subgroup of query objects and the data object that optimizes the aggregate cost function for a given subgroup size m (m <= n), and (iii) the multiple subgroup nearest neighbor with keywords query, which finds optimal subgroups and corresponding data objects for each of the subgroup sizes in the range [m, n]. We design query processing algorithms based on branch-and-bound and best-first paradigms. Finally, we conduct extensive experiments with two real datasets to show the efficiency of the proposed algorithms.