In this paper, we proposed an interactive knowledge-based method for graph summarization. Due to the interactive nature of this method, the user can decide to stop or continue summarization process at any step based on the summary graph. The proposed method is a general More
In this paper, we proposed an interactive knowledge-based method for graph summarization. Due to the interactive nature of this method, the user can decide to stop or continue summarization process at any step based on the summary graph. The proposed method is a general one that covers three kinds of graph summarization called structural, attribute-based, and structural/attribute-based summarization. In summarization based on both structure and vertex attributes, the contributions of syntactical and semantical attributes, as well as the importance degrees of attributes are variable and could be specified by the user. We also proposed a new criterion based on density and entropy to assess the quality of a hybrid summary. For the purpose of evaluation, we generated a synthetic graph with 1000 nodes and 2500 edges and extracted the overall features of the graph using the Gephi tool and a developed application in Java. Finally, we generated summaries of different sizes and values for the structure contribution (α parameter). We calculated the values of density and entropy for each summary to assess their qualities based on the proposed criterion. The experimental results show that the proposed criterion causes to generate a summary with better quality.
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