A Top-r k Influential Community Search Algorithm

摘要

Top-r k influential community search is one of the hot topics in social network research, the solution of which usually adapts the "index+query" strategy. Aiming at the problems of low index efficiency and unreasonable metric of the influence, we first propose a new index construction method that not only improves the efficiency of constructing index but also reduces the index size. In the community search, the metric of the influence on the community is redefined and the search algorithm is proposed on this basis to make the search results more practical. Finally, according to experiments on 12 datasets, we verify the high efficiency of the method proposed in this paper compared with the existing methods from the following aspects including the index construction time, the index size, and the search time.