Enhanced Algorithms for Counting Rectangles in Large Bipartite Graphs using MapReduce | ||||
| Mansoura Journal for Computer and Information Sciences | ||||
| Volume 14, Issue 1, June 2018, Page 61-66 PDF (693.64 K) | ||||
| Document Type: Original Research Articles. | ||||
| DOI: 10.21608/mjcis.2018.311999 | ||||
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| Authors | ||||
| Ahmed T. Sharafeldeen; Mohammed F. Alrahmawy; Samir Elmougy | ||||
| Faculty of computers and information systems, C.S dep. Mansoura University, Egypt | ||||
| Abstract | ||||
| Rectangles for bipartite graphs are like triangles for unipartite graphs as both represent the smallest cycles in such graphs. Rectangle Counting is considered an important task in many bipartite network analysis metrics and is considered the core of computing such metrics, especially in cluster coefficient, bitruss, etc. However, there are few efficient algorithms to deal with this problem, especially in a large bipartite graph. In this work, we use MapReduce to enhance an algorithm to count rectangles in a large bipartite graph. The results show that our proposed MapReduce-based algorithm gives a better execution time than the existing algorithms, especially when it is applied in very large bipartite graphs | ||||
| Keywords | ||||
| Rectangle Counting; Bipartite Graph; MapReduce; LargeScale Graph Analysis | ||||
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