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Discovering Communities of Users on Social Networks Based on Topic Model Combined with Kohonen Network

机译:基于主题模型与kohonen网络一起发现用户社区社区

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Interaction among users on social networks through messages and interested topics forms online communities. The question is how to discover what communities users belong to or what online communities are interested in or what each period of time the interested topic change in online communities are? To answer these questions, this paper proposes a new model for discovering communities on social networks based on the topic model combined with Kohonen networks. This model, we focus on discovering online communities and surveying the changes in interested topic and users in communities with temporal factor. The proposed model is experimented with a set of interested topic vectors. These topics are exploited from a corpus of messages in Vietnamese on social networks in the higher education field.
机译:通过消息和感兴趣的主题在社交网络上的互动形成在线社区。问题是如何了解社区用户所属的或在线社区中感兴趣的主题更改的所有时间何种内容?要回答这些问题,本文提出了一种基于主题模型与科霍恩网络相结合的社交网络社区的新模式。这一模型,我们专注于发现在线社区,并调查涉及时间因素的兴趣主题和用户的变化。建议的模型进行了一组感兴趣的主题向量。这些主题是从高等教育领域的社交网络中的越南语中的一部分消息中利用。

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