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Semantic community detection using label propagation algorithm

机译:使用标签传播算法的语义社区检测

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摘要

The issue of detecting large communities in online social networks is the subject of a wide range of studies in order to explore the network sub-structure. Most of the existing studies are concerned with network topology with no emphasis on active communities among the large online social networks and social portals, which are not based on network topology like forums. Here, new semantic community detection is proposed by focusing on user attributes instead of network topology. In the proposed approach, a network of user activities is established and weighted through semantic data. Furthermore, consistent extended label propagation algorithm is presented. Doing so, semantic representations of active communities are refined and labelled with user-generated tags that are available in web.2. The results show that the proposed semantic algorithm is able to significantly improve the modularity compared with three previously proposed algorithms.
机译:为了探索网络子结构,在线社交网络中检测大型社区的问题是广泛研究的主题。现有的大多数研究都与网络拓扑有关,而不关注大型在线社交网络和社交门户中的活跃社区,这些社区不基于论坛等网络拓扑。这里,通过关注用户属性而不是网络拓扑来提出新的语义社区检测。在提出的方法中,通过语义数据建立用户活动网络并对其进行加权。此外,提出了一致的扩展标签传播算法。这样做,可以完善活动社区的语义表示,并使用在web.2中可用的用户生成的标签进行标记。结果表明,与先前提出的三种算法相比,所提出的语义算法能够显着提高模块性。

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