Community mining on non-binary graph sequences
Songcan Chen · Journal of Shandong University · 2011
Against the defects of existing graph sequences community mining methods,a community mining method on non-binary graph sequences based on the minimum description length principle was proposed.According to its nature of complete NP-hard problem,it was processed by preprocessing on the problem and a relatively good initial input was obtained.Based on the concept of graph sequences coding length,an optimization problem was solved by regrouping rows and columns to integrate gray information.And then a community mining problem was effectively solved.It could avoid being trapped in the local minimum by using the random and optimization mind of genetic algorithm in the processing.In addition,the change of community structure could be detected with passage of time which is critical for reality problems.Finally,an experiment validated the effectiveness of this method and its high performance.