Distributed Graph Summarization.
CIKM '14: 2014 ACM Conference on Information and Knowledge Management Shanghai China November, 2014(2014)
摘要
Graph has been a ubiquitous and essential data representation to model real world objects and their relationships. Today, large amounts of graph data have been generated by various applications. Graph summarization techniques are crucial in uncovering useful insights about the patterns hidden in the underlying data. However, all existing works in graph summarization are single-process solutions, and as a result cannot scale to large graphs. In this paper, we introduce three distributed graph summarization algorithms to address this problem. Experimental results show that the proposed algorithms can produce good quality summaries and scale well with increasing data sizes. To the best of our knowledge, this is the first work to study distributed graph summarization methods.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络