Abstract—The data in many disciplines such as social net-works, web analysis, etc. is link-based, and the link structure can be exploited for many different data mining tasks. In this paper, we consider the problem of temporal link prediction: Given link data for time periods 1 through T, can we predict the links in time period T+1? Specifically, we look at bipartite graphs changing over time and consider matrix- and tensor-based methods for predicting links. We present a weight-based method for collapsing multi-year data into a single matrix. We show how the well-known Katz method for link prediction can be extended to bipartite graphs and, moreover, approximated in a scalable way using a truncated singular value decomposition. Using a CAN...
Abstract. This paper aims at the problem of link pattern prediction in collections of objects connec...
Through several studies, it has been highlighted that mobility patterns in mobile networks are drive...
The problem of information network analysis has gained increasing attention in recent years, because...
International audienceIn this paper we address the problem of temporal link prediction, i.e., predic...
We study temporal link prediction problem, where, given past interactions, our goal is to predict ne...
The increasing interest in dynamically changing networks has led to growing interest in a more gener...
Link prediction is a task in Social Network Analysis that consists of predicting connections that ar...
n recent years, link prediction has been applied to a wide range of real-world applications which of...
The question of how to predict which links will form in a graph, given the graph's history, is an op...
Abstract—In user-item networks, the link prediction problem has received considerable attentions and...
We propose a new method for characterizing the dynamics of complex networks with its application to ...
Many real world, complex phenomena have an underlying structure of evolving networks where nodes and...
The link prediction problem can be used for predicting the link changes that are difficult to unders...
Understanding the evolutionary patterns of real-world complex systems such as human interactions, bi...
There is an increasing attention towards link prediction in complex networks both in physical and co...
Abstract. This paper aims at the problem of link pattern prediction in collections of objects connec...
Through several studies, it has been highlighted that mobility patterns in mobile networks are drive...
The problem of information network analysis has gained increasing attention in recent years, because...
International audienceIn this paper we address the problem of temporal link prediction, i.e., predic...
We study temporal link prediction problem, where, given past interactions, our goal is to predict ne...
The increasing interest in dynamically changing networks has led to growing interest in a more gener...
Link prediction is a task in Social Network Analysis that consists of predicting connections that ar...
n recent years, link prediction has been applied to a wide range of real-world applications which of...
The question of how to predict which links will form in a graph, given the graph's history, is an op...
Abstract—In user-item networks, the link prediction problem has received considerable attentions and...
We propose a new method for characterizing the dynamics of complex networks with its application to ...
Many real world, complex phenomena have an underlying structure of evolving networks where nodes and...
The link prediction problem can be used for predicting the link changes that are difficult to unders...
Understanding the evolutionary patterns of real-world complex systems such as human interactions, bi...
There is an increasing attention towards link prediction in complex networks both in physical and co...
Abstract. This paper aims at the problem of link pattern prediction in collections of objects connec...
Through several studies, it has been highlighted that mobility patterns in mobile networks are drive...
The problem of information network analysis has gained increasing attention in recent years, because...