Add to ORKGAbstract. Understanding the structures why links are formed is an important and prominent research topic. In this paper, we therefore consider the link prediction problem in face-to-face contact networks, and analyze the predictability of new and recurring links. Furthermore, we study additional influence factors, and the role of stronger ties in these networks. Specifically, we compare neighborhood-based and path-based network proximity measures in a threshold-based analysis for capturing temporal dynamics. The results and insights of the analysis are a first step onto predictability applications for human contact networks, for exam-ple, for improving recommendations.
© 2019 Elsevier B.V. Link prediction in social networks has a long history in complex network resear...
Link prediction is a problem of predicting future edges of an undirected graph based on a single sna...
Link prediction is a “hot topic” in network analysis and has been largely used for friendship recomm...
The prediction of new links in social networks is a challeng- ing task. In this paper, we focus on p...
International audienceThe prediction of new links in social networks is a challenging task. In this ...
Given a snapshot of a social network, can we infer which new interactions among its members are like...
Research on link prediction for social networks has been actively pursued. In link prediction for a ...
Research on link prediction for social networks has been actively pursued. In link prediction for a ...
A social network can have many different types of links or margins between nodes. Those, for example...
The automated analysis of social networks has become an important problem due to the pro-liferation ...
In a social network there can be many different kind of links or edges between the nodes. Those coul...
Recommendation systems based on historical action logs between users and items are usually formulate...
The link prediction problem can be used for predicting the link changes that are difficult to unders...
Link prediction aims to identify unknown or missing connections in a network. The methods based on n...
Link prediction is the problem of inferring new relationships among nodes in a network that are like...
© 2019 Elsevier B.V. Link prediction in social networks has a long history in complex network resear...
Link prediction is a problem of predicting future edges of an undirected graph based on a single sna...
Link prediction is a “hot topic” in network analysis and has been largely used for friendship recomm...
The prediction of new links in social networks is a challeng- ing task. In this paper, we focus on p...
International audienceThe prediction of new links in social networks is a challenging task. In this ...
Given a snapshot of a social network, can we infer which new interactions among its members are like...
Research on link prediction for social networks has been actively pursued. In link prediction for a ...
Research on link prediction for social networks has been actively pursued. In link prediction for a ...
A social network can have many different types of links or margins between nodes. Those, for example...
The automated analysis of social networks has become an important problem due to the pro-liferation ...
In a social network there can be many different kind of links or edges between the nodes. Those coul...
Recommendation systems based on historical action logs between users and items are usually formulate...
The link prediction problem can be used for predicting the link changes that are difficult to unders...
Link prediction aims to identify unknown or missing connections in a network. The methods based on n...
Link prediction is the problem of inferring new relationships among nodes in a network that are like...
© 2019 Elsevier B.V. Link prediction in social networks has a long history in complex network resear...
Link prediction is a problem of predicting future edges of an undirected graph based on a single sna...
Link prediction is a “hot topic” in network analysis and has been largely used for friendship recomm...