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Variational Approach for Learning Community Structures
المؤلفون المشاركون
Choong, Jun Jin
Liu, Xin
Murata, Tsuyoshi
المصدر
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-12-13
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
Discovering and modeling community structure exist to be a fundamentally challenging task.
In domains such as biology, chemistry, and physics, researchers often rely on community detection algorithms to uncover community structures from complex systems yet no unified definition of community structure exists.
Furthermore, existing models tend to be oversimplified leading to a neglect of richer information such as nodal features.
Coupled with the surge of user generated information on social networks, a demand for newer techniques beyond traditional approaches is inevitable.
Deep learning techniques such as network representation learning have shown tremendous promise.
More specifically, supervised and semisupervised learning tasks such as link prediction and node classification have achieved remarkable results.
However, unsupervised learning tasks such as community detection remain widely unexplored.
In this paper, a novel deep generative model for community detection is proposed.
Extensive experiments show that the proposed model, empowered with Bayesian deep learning, can provide insights in terms of uncertainty and exploit nonlinearities which result in better performance in comparison to state-of-the-art community detection methods.
Additionally, unlike traditional methods, the proposed model is community structure definition agnostic.
Leveraging on low-dimensional embeddings of both network topology and feature similarity, it automatically learns the best model configuration for describing similarities in a community.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Choong, Jun Jin& Liu, Xin& Murata, Tsuyoshi. 2018. Variational Approach for Learning Community Structures. Complexity،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1134406
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Choong, Jun Jin…[et al.]. Variational Approach for Learning Community Structures. Complexity No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1134406
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Choong, Jun Jin& Liu, Xin& Murata, Tsuyoshi. Variational Approach for Learning Community Structures. Complexity. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1134406
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1134406
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
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