@article{adr-networking-communication-eng, author = {Yogita Shewale}, title = { A Study of User Strength Forecast, Ranking and as long as Ads in Social Networking Services Built on Users Profile}, journal = {Journal of Advanced Research in Networking and Communication Engineering}, volume = {2}, number = {2}, year = {2021}, keywords = {}, abstract = {In proposed system, there is a single point of view to complete this objective, which is quantifying user vitality by investigative the dynamic interactions among users on social networks and their profiles. The social networking service facilitates the building of social networks or social relations among users who, for instance, share interest, activities, and background and physical connections. Through such service, users could stay connected with each other and be informed of friend’s behaviors such as posting at a platform, and consequently be inclined by each other. Hence proposed system is a novel strategy to learn the latent profiles of social users rank them and recommend ads. To evaluate the performance of proposed algorithms collected dynamic social network data sets. The experimental results with data set clearly demonstrate the advantage of prediction methods and proposed ranking. How to cite this article:Shewale Y, Dholi PR. A Study of User Strength Forecast, Ranking and as long as Ads in Social Networking Services Built on Users Profile. J Adv Res Netw Comm Engg 2019; 2(2): 14-16.}, pages = {14--16}, url = {http://thejournalshouse.com/index.php/adr-networking-communication-eng/article/view/380} }