并行算法，以找到社区使用Jaccard度量

2015 IEEE International Conference on Electro/Information Technology (EIT) Pub Date : 2015-05-21 DOI:10.1109/EIT.2015.7293371

J. Scripps, C. Trefftz

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引用次数: 3

摘要

给定一个图，在图中寻找社区有许多不同的原因。已经提出了许多算法来寻找图上的社区。其中许多算法都很耗时。在植物物种地理位置的背景下引入的Jaccard度量已被用于寻找群落。使用OpenMP对基于Jaccard度量的社区查找算法进行了并行化处理。报告性能结果。

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Parallelizing an algorithm to find communities using the Jaccard metric

Given a graph, there are many different reasons for finding communities in a graph. Numerous algorithms have been proposed for finding communities on graphs. Many of those algorithms are time consuming. The Jaccard metric, introduced in the context of the geographic location of botanical species, has been used to find communities. An algorithm to find communities based on the Jaccard metric was parallelized using OpenMP. Performance results are reported.

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2015 IEEE International Conference on Electro/Information Technology (EIT)

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