Maximal clique analysis is an important method of stock market graph analysis. Traditional maximal clique enumeration algorithms enumerate all maximal cliques in the graph, which cannot support efficient stock market graph analysis. In this paper, we propose interactive visualization methods for large-scale stock market graphs. According to user’s interested stocks, we provide functions to enumerate all maximal cliques related to those stocks quickly, and to view their combination relations as well as other related stocks. Our interactive visualization methods are very useful to stock market graph analysis. Moreover, traditional maximal clique enumeration algorithms cannot be applied to support those functions. Due to the need of enumerating all maximal cliques related to specific nodes or edges, we propose a new maximal clique enumeration algorithm containing specific nodes or edges. We use real a dataset to verify the superior performance of our algorithm.
Citing format Tu ZhiBing, Cheng Jie Feng, Feng Sheng-zhong. On Interactive Visualization for Large-Scale Stock Market Graphs[J]. Journal of Integration Technology,2013,2(1):8-15