A SURVEY ON LINK PREDICTION WITH OR WITHOUT TIME AWARE FEATURE IN SOCIAL NETWORK

Online network systems have become popular in many social, biological and information system in recent year. Much research has been done in social network, which is increasingly growing and form a large complex network. Social network such as Facebook provides a platform for users to share their interest, photos & post etc with their friend. A social network can be well described by a network graph, in which node represents users and edges between nodes represent some association. In most social network links are dynamics and change over the time in network. To predict an association between two nodes in a graph, which is likely to be occur in near future and is termed as link prediction. Many approach and method have been used for predicting a link in past years, a significant interest of the methods uses local and global structure of the graph to make predictions. In this survey we are highlighting the impact of time in association (collaboration or interaction) & temporal behavior of the link between the nodes in link prediction. In this Survey we summarized link prediction without temporal features and Link prediction with time aware features, particularly the relationship between the time stamps of interactions or links and how link strength affects future link creation