Mining networks with shared items

Recent advances in data processing have enabled the generation of large and complex graphs. Many researchers have developed techniques to investigate informative structures within these graphs. However, the vertices and edges of most real-world graphs are associated with its features, and only a few studies have considered their combination. In this paper, we specifically examine a large graph in which each vertex has associated items. From the graph, we extract subgraphs with common itemsets, which we call itemset-sharing subgraphs (ISSes). The problem has various potential applications such as the detection of gene networks affected by drugs or the findings of popular research areas of contributing researchers. We propose an efficient algorithm to enumerate ISSes in large graphs. This algorithm enumerates ISSes with two efficient data structures: a DFS itemset tree and a visited itemset table. In practice, the combination of these two structures enables us to compute optimal solutio...

• Type: Journal
• Year: 2010
• Where: CIKM
• Authors: Jun Sese, Mio Seki, Mutsumi Fukuzaki
• Keywords: Algorithms, CIKM 2010, Efficient Data Structures, Information Technology, Large Graphs