Context-aware query aims to make the user get suitable query results based on the users' contexts. When a user as a leader or a representative issues a query, s/he often needs to consider a group of people. To this end, context-aware database should meet most of the people's contexts in this situation. In this paper, we propose an approximation algorithm to compute context-aware group top-k query results. Moreover, we optimize the algorithm by clustering the users inside the group. The experimental results show that our algorithm is quite efficient and effective.
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