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; …
Computational network biology: data, models, and applications
Biological entities are involved in intricate and complex interactions, in which uncovering the
biological information from the network concepts are of great significance. Benefiting from …
biological information from the network concepts are of great significance. Benefiting from …
Link prediction by deep non-negative matrix factorization
G Chen, H Wang, Y Fang, L Jiang - Expert Systems with Applications, 2022 - Elsevier
Link prediction aims to predict missing links or eliminate spurious links and new links in
future network by known network structure information. Most existing link prediction methods …
future network by known network structure information. Most existing link prediction methods …
Link prediction via matrix completion
Inspired by the practical importance of social networks, economic networks, biological
networks and so on, studies on large and complex networks have attracted a surge of …
networks and so on, studies on large and complex networks have attracted a surge of …
A nonuniform popularity-similarity optimization (nPSO) model to efficiently generate realistic complex networks with communities
A Muscoloni, CV Cannistraci - New Journal of Physics, 2018 - iopscience.iop.org
The investigation of the hidden metric space behind complex network topologies is a fervid
topic in current network science and the hyperbolic space is one of the most studied …
topic in current network science and the hyperbolic space is one of the most studied …
A novel graph mining approach to predict and evaluate food-drug interactions
MM Rahman, SM Vadrev, A Magana-Mora, J Levman… - Scientific reports, 2022 - nature.com
Food-drug interactions (FDIs) arise when nutritional dietary consumption regulates
biochemical mechanisms involved in drug metabolism. This study proposes FDMine, a …
biochemical mechanisms involved in drug metabolism. This study proposes FDMine, a …
Nonnegative matrix factorization for link prediction in directed complex networks using PageRank and asymmetric link clustering information
G Chen, C Xu, J Wang, J Feng, J Feng - Expert Systems with Applications, 2020 - Elsevier
The aim of link prediction is to predict missing links in current networks or new links in future
networks. Almost all the existing directed link prediction algorithms only take into account the …
networks. Almost all the existing directed link prediction algorithms only take into account the …
Link prediction based on spectral analysis
C Gui - Plos one, 2024 - journals.plos.org
Link prediction in complex network is an important issue in network science. Recently,
various structure-based similarity methods have been proposed. Most of algorithms are …
various structure-based similarity methods have been proposed. Most of algorithms are …
Complex systems and network science: a survey
K Yang, J Li, M Liu, T Lei, X Xu, H Wu… - Journal of systems …, 2023 - ieeexplore.ieee.org
Complex systems widely exist in nature and human society. There are complex interactions
between system elements in a complex system, and systems show complex features at the …
between system elements in a complex system, and systems show complex features at the …
Pioneering topological methods for network-based drug–target prediction by exploiting a brain-network self-organization theory
The bipartite network representation of the drug–target interactions (DTIs) in a biosystem
enhances understanding of the drugs' multifaceted action modes, suggests therapeutic …
enhances understanding of the drugs' multifaceted action modes, suggests therapeutic …