  Community detection and link prediction are both of great significance in
network analysis, which provide very valuable insights into topological
structures of the network from different perspectives. In this paper, we
propose a novel community detection algorithm with inclusion of link
prediction, motivated by the question whether link prediction can be devoted to
improving the accuracy of community partition. For link prediction, we propose
two novel indices to compute the similarity between each pair of nodes, one of
which aims to add missing links, and the other tries to remove spurious edges.
Extensive experiments are conducted on benchmark data sets, and the results of
our proposed algorithm are compared with two classes of baseline. In
conclusion, our proposed algorithm is competitive, revealing that link
prediction does improve the precision of community detection.
