Abstract
With the advent of the Internet, online social networks are furiously growing and influencing our daily life. In this work, we have worked upon the problem of link prediction across nodes within these growing online social networks. Prediction of link within the social network is pertaining to missing and future links in the network in future. This could be attained by topological attributes or measures that collaborated with machine learning approaches. In this paper, we have tried to develop an edge prediction model which will be trained using a supervised machine learning technique. For experimental analysis, Wikipedia network has been used.
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Bhanodia, P.K., Khamparia, A., Pandey, B. (2021). An Approach to Predict Potential Edges in Online Social Networks. In: Jat, D.S., Shukla, S., Unal, A., Mishra, D.K. (eds) Data Science and Security. Lecture Notes in Networks and Systems, vol 132. Springer, Singapore. https://doi.org/10.1007/978-981-15-5309-7_1
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DOI: https://doi.org/10.1007/978-981-15-5309-7_1
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