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Towards Bipartite Graph Data Management

机译:向两分图数据管理

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Bipartite graphs are widely used to model social networks and web data. However bipartite graph data management (BGDM for short) is not fully studied. Without appropriate indexing structures, query and analysis operations on bipartite graphs are not efficient. In this paper, we raise the issues of BGDM and present architecture of BGDM. Then we propose a logic graph structure (i.e., star) for indexing bipartite graph to improve common operations efficiently. Furthermore, we propose a star-based block structure to store bipartite graphs and the relevant query algorithm. The star-based method may avoid loading the whole block for vertex queries using Bloom filter. Finally, our experiments show that the block design is effective and feasible for vertex query algorithm.
机译:二角形图广泛用于建模社交网络和Web数据。然而,没有完全研究二分层图数据管理(简短的BGDM)。如果没有适当的索引结构,则对二角形图的查询和分析操作并不有效。在本文中,我们提出了BGDM的问题和BGDM的现状。然后,我们提出了一种逻辑图结构(即,星星),用于索引双链图,以有效地改善常见操作。此外,我们提出了一种基于星形的块结构来存储二分图和相关查询算法。基于明星的方法可以避免使用Bloom Filter加载用于顶点查询的整个块。最后,我们的实验表明,块设计对于Vertex查询算法是有效和可行的。

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