Abstract: The present invention discloses a method for detecting the community structure in complicated networks. In order to improve the global convergence performance of the differential evolution algorithm, three main evolution operations are redesigned, including a classification-based adaptive mutation strategy, a dynamic adaptive parameter adjustment strategy, and a historical information-based selection operation. On the other hand, in order to make better use of the network topology information, the present invention provides a neighborhood information-based improved community adjustment strategy to ensure that sufficient search space is provided for the global optimal community division, while reducing the search space of DE. Finally, the present invention provides a new modularity optimization algorithm CDEMO based on differential evolution algorithm.

Abstract: Social relationship chain obtaining method and terminal and a readable medium are provided. The method includes: obtaining a target user set and mutual-friend information between any two target users in the target user set, target users in the target user set being friends of a center user, and the mutual-friend information indicating whether the two target users are in a friend relationship; constructing a reference network according to the center user and the mutual-friend information between the any two target users in the target user set, nodes in the reference network being the target users in the target user set, and there being a connection line between two target users in the reference network that are in a friend relationship; and determining, from the target user set according to the reference network, a target user being in a parent-child relationship chain with the center user.