TY - EJOU
AU - Jiang, Yirong
AU - Jiang, Weijin
AU - Chen, Jiahui
AU - Wang, Yang
AU - Xu, Yuhui
AU - Tan, Lina
AU - Guo, Liang
TI - A New Method Based on Evolutionary Algorithm for Symbolic Network Weak Unbalance
T2 - Journal on Internet of Things
PY - 2019
VL - 1
IS - 2
SN - 2579-0080
AB - The symbolic network adds the emotional information of the relationship, that is, the “+” and “-” information of the edge, which greatly enhances the modeling ability and has wide application in many fields. Weak unbalance is an important indicator to measure the network tension. This paper starts from the weak structural equilibrium theorem, and integrates the work of predecessors, and proposes the weak unbalanced algorithm EAWSB based on evolutionary algorithm. Experiments on the large symbolic networks Epinions, Slashdot and WikiElections show the effectiveness and efficiency of the proposed method. In EAWSB, this paper proposes a compression-based indirect representation method, which effectively reduces the size of the genotype space, thus making the algorithm search more complete and easier to get better solutions.
KW - Weak structural balance
KW - signed networks
KW - evolutionary algorithms
KW - incremental computation
KW - compressed representation
DO - 10.32604/jiot.2019.07231