Due to the growing interest in social networks, link prediction has received significant attention. Link prediction is mostly based on graph-based features, with some recent approaches focusing on domain semantics. We ...

Link prediction in a network is mostly based on information about the neighborhood topology of the nodes. Recently, the interest for hybrid link prediction approaches that combine topology information with information about ...

This thesis aims to contribute to the literature on text-based link prediction methods in scientific collaboration networks with two original works. First, in Chapter I we present a comprehensive survey on text-based link ...

Users of online social networks voluntarily participate in different user groups or communities. Researches suggest the presence of strong local community structure in these social networks, i.e., users tend to meet other ...

Link prediction in online social networks is useful in numerous applications, mainly for recommendation. Recently, different approaches have considered friendship groups information for increasing the link prediction ...

Many real-world domains are relational in nature since they consist of a set of objects related to each other in complex ways. However, there are also flat data sets and if we want to apply graph-based algorithms, it is ...

In addition to being in contact with friends, online social networks are commonly used as a source of information, suggestions and recommendations from members of the community. Whenever we accept a suggestion or perform ...

The task of determining whether or not a link will exist between two entities, given the current position of the network, is called link prediction. The study of predicting and analyzing links between entities in a network ...