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Link Prediction in Social Network using Artificial Neural Network

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Anjali Sharma, Sneha Soni, Kalpana Rai

Anjali Sharma, Sneha Soni and Kalpana Rai. Link Prediction in Social Network using Artificial Neural Network. International Journal of Computer Applications 174(32):26-30, April 2021. BibTeX

	author = {Anjali Sharma and Sneha Soni and Kalpana Rai},
	title = {Link Prediction in Social Network using Artificial Neural Network},
	journal = {International Journal of Computer Applications},
	issue_date = {April 2021},
	volume = {174},
	number = {32},
	month = {Apr},
	year = {2021},
	issn = {0975-8887},
	pages = {26-30},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2021921210},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


The prediction process from prior information of the event helps to know the evolution of social network and assists the companies in effective decisions making during a typical recommendation system. Social network connection prediction is an efficient technique for the analysis of the evolution of social organizations and formation of the social network relations. Link prediction is a crucial research direction within the field of complex networks and data processing. In this work, we proposed a technique which is based on node similarity measure and Artificial Neural Network concept. We consider the features or information which are available in data set then assign the score to all pairs of nodes and apply Artificial Neural Network concept to the system. The proposed technique will improve the accuracy of Link Prediction.


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Social Networks, Link Prediction, Neighbourhood Tightness, Machine Learning, Supervised Algorithm, Unsupervised Algorithm, SVM, ANN.