Abstract
Social Network, the most popular Internet service, has a miracle rapid increment of number of users in recent years. In this paper, we present how to use SOM network to cluster the actor based on vector. This vector is a distribution probability of topic that actor prefers. We use ART model to create the vector of interested topics. Moreover, we use Enron email corpus as a sample dataset to evaluate efficiency in SOM network. By experimenting on the dataset, we demonstrate that our proposed model can be used to extract well and meaningful cluster following the topics. We use F – measure method for this application for testing precision of SOM algorithm. As a result, from our sample tests, the F-measure cites the acceptable accuracy of the SOM method. Based on the result, application developers can use SOM to group the actors based on their interested topics.
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Tran Quang, H., Vo Ho Tien, H., Nguyen Le, H., Ho Trung, T., Do, P. (2014). Finding the Cluster of Actors in Social Network Based on the Topic of Messages. In: Nguyen, N.T., Attachoo, B., Trawiński, B., Somboonviwat, K. (eds) Intelligent Information and Database Systems. ACIIDS 2014. Lecture Notes in Computer Science(), vol 8397. Springer, Cham. https://doi.org/10.1007/978-3-319-05476-6_19
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DOI: https://doi.org/10.1007/978-3-319-05476-6_19
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05475-9
Online ISBN: 978-3-319-05476-6
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