Link prediction techniques, applications, and performance: A survey
Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
A survey of link prediction in complex networks
Networks have become increasingly important to model complex systems composed of
interacting elements. Network data mining has a large number of applications in many …
interacting elements. Network data mining has a large number of applications in many …
Continuous-time dynamic network embeddings
Networks evolve continuously over time with the addition, deletion, and changing of links
and nodes. Although many networks contain this type of temporal information, the majority of …
and nodes. Although many networks contain this type of temporal information, the majority of …
Robust graph regularization nonnegative matrix factorization for link prediction in attributed networks
Link prediction is one of the most widely studied problems in the area of complex network
analysis, in which machine learning techniques can be applied to deal with it. The biggest …
analysis, in which machine learning techniques can be applied to deal with it. The biggest …
Random walks: A review of algorithms and applications
A random walk is known as a random process which describes a path including a
succession of random steps in the mathematical space. It has increasingly been popular in …
succession of random steps in the mathematical space. It has increasingly been popular in …
A review of relational machine learning for knowledge graphs
Relational machine learning studies methods for the statistical analysis of relational, or
graph-structured, data. In this paper, we provide a review of how such statistical models can …
graph-structured, data. In this paper, we provide a review of how such statistical models can …
Link prediction in social networks: the state-of-the-art
In social networks, link prediction predicts missing links in current networks and new or
dissolution links in future networks, is important for mining and analyzing the evolution of …
dissolution links in future networks, is important for mining and analyzing the evolution of …
Link prediction in complex networks: A survey
L Lü, T Zhou - Physica A: statistical mechanics and its applications, 2011 - Elsevier
Link prediction in complex networks has attracted increasing attention from both physical
and computer science communities. The algorithms can be used to extract missing …
and computer science communities. The algorithms can be used to extract missing …
Identifying influential nodes in complex networks
Identifying influential nodes that lead to faster and wider spreading in complex networks is of
theoretical and practical significance. The degree centrality method is very simple but of little …
theoretical and practical significance. The degree centrality method is very simple but of little …