Abstract
This research shows how to find missing or soon-to-appear links using a community-based link prediction approach. In the large-scale distribution of information, online social networks play a key role. Many attempts have been made to understand this phenomenon, ranging from the detection of hot topics to the modelling of information distribution, including the identification of influential spreaders. Using a community-based link prediction method, missing links were identified based on an information diffusion algorithm. First, we show when using a community discovery approach to split the network into clusters. Afterwards when a unique approach based on information diffusion and community structure is presented to anticipate target links. Finally, to improve the accuracy of the current approach, we are using the graph convolution network
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Samuel, L., Ashok, A. (2023). Missing Link Prediction in the Social Network Using Graph Convolutional Networks. In: Tuba, M., Akashe, S., Joshi, A. (eds) ICT Infrastructure and Computing. Lecture Notes in Networks and Systems, vol 520. Springer, Singapore. https://doi.org/10.1007/978-981-19-5331-6_41
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DOI: https://doi.org/10.1007/978-981-19-5331-6_41
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