A generative model for dynamic networks with applications

Gupta, S and Sharma, G and Dukkipati, A (2019) A generative model for dynamic networks with applications. In: 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence,, 27 January 2019 - 1 February 2019, Honolulu, pp. 7842-7849.

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Abstract

Networks observed in real world like social networks, collaboration networks etc., exhibit temporal dynamics, i.e. nodes and edges appear and/or disappear over time. In this paper, we propose a generative, latent space based, statistical model for such networks (called dynamic networks). We consider the case where the number of nodes is fixed, but the presence of edges can vary over time. Our model allows the number of communities in the network to be different at different time steps. We use a neural network based methodology to perform approximate inference in the proposed model and its simplified version. Experiments done on synthetic and real world networks for the task of community detection and link prediction demonstrate the utility and effectiveness of our model as compared to other similar existing approaches.

Item Type:	Conference Paper
Publication:	33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
Publisher:	AAAI Press
Additional Information:	The copyright for this article belongs to AAAI Press.
Keywords:	Artificial intelligence, Approximate inference; Collaboration network; Community detection; Different time steps; Generative model; Real-world networks; Statistical modeling; Temporal dynamics, Neural networks
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	01 Dec 2022 07:06
Last Modified:	01 Dec 2022 07:06
URI:	https://eprints.iisc.ac.in/id/eprint/78129

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