| Abstrakt: |
Community discovery can reveal the topology and important nodes of real social networks. Due to its linear time complexity and no need to define objective functions and objective parameters, Label Propagation Algorithm (LPA) is widely used in academic and practical fields as a classic community discovery algorithm. Aiming at the update disorder of LPA algorithm and the randomness of label selection, a Rational Node Label Propagation Algorithm Based on Node Influence (RLPBNI) is proposed. The algorithm takes the node influence ranking as the update order, introduces the concept of rational nodes for label selection, and defines the overlap degree for community dimensionality reduction. The analysis of the experimental results shows that, compared with other comparative algorithms, the RLPBNI algorithm can not only effectively improve the accuracy of community division, but also more easily discover hidden communities in networks with a high degree of mixing. [ABSTRACT FROM AUTHOR] |
