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Link prediction approach to recommender systems
The problem of recommender system is very popular with myriad available solutions. Recommender systems recommend items to users and help them in...
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Cross-KG Link Prediction by Learning Substructural Semantics
Link prediction across different knowledge graphs (i.e. Cross-KG link prediction) plays an important role in discovering new triples and fusing...
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A comprehensive survey of link prediction methods
Link prediction aims to anticipate the probability of a future connection between two nodes in a given network based on their previous interactions...
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Missing link prediction using path and community information
Due to the evolving nature of complex networks, link prediction plays a crucial role in exploring likelihood of potential relationships among nodes....
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MHRE: Multivariate link prediction method for medical hyper-relational facts
AbstractAs hyper-relational facts continue to proliferate within knowledge graphs, link prediction on binary relations has become inadequate, while...
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A link prediction method based on compressed sensing for social networks
Link prediction is an important task in social network analysis, with the goal of evaluating the possibility of forming links between node pairs. In...
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A novel and precise approach for similarity-based link prediction in diverse networks
In recent times, real-world systems have been rapidly growing in size resulting in increased complexity. Networks are an interpretation of the...
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Interlayer co-similarity matrices for link prediction in multiplex networks
Given a target layer in a multiplex network, the objective of link prediction is to predict future relationships by utilizing information from all...
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Personalized sampling graph collection with local differential privacy for link prediction
Link prediction (LP) is an attractive research problem on social network data. Yet, the link information may be leaked by the untrusted collector. As...
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Unraveling human social behavior motivations via inverse reinforcement learning-based link prediction
Link prediction aims to capture the evolution of network structure, especially in real social networks, which is conducive to friend recommendations,...
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Backdoor Attack on Dynamic Link Prediction
Based on historical information, graph prediction is performed by Dynamic Link Prediction (DLP). The quality of the training data plays a crucial...
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Link-Aware Link Prediction over Temporal Graph by Pattern Recognition
A temporal graph can be considered as a stream of links, each of which represents an interaction between two nodes at a certain time. On temporal...
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Link prediction in social networks using hyper-motif representation on hypergraph
Link prediction, a critical pursuit in complex networks research, revolves around the predictive understanding of connections between nodes. Our...
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DynamiSE: dynamic signed network embedding for link prediction
In real-world scenarios, dynamic signed networks are ubiquitous where edges have positive and negative types and evolve over time. Graph neural...
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Deep non-negative matrix factorization with edge generator for link prediction in complex networks
AbstractLink prediction aims to infer missing links or predict future links based on observed topology or attribute information in the network. Many...
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Dynamic relation learning for link prediction in knowledge hypergraphs
Link prediction for knowledge graphs (KGs), which aims to predict missing facts, has been broadly studied in binary relational KGs. However, real...
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Improved artificial bee colony algorithm based on community detection for link prediction problem
The problem of link prediction has recently gained a lot of attention from various domains, including sociology, anthropology, information science,...
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A Deep Learning Framework for Dynamic Network Link Prediction
Link prediction, which involves predicting potential relations between nodes in networks, has long been a challenge in network science. Most studies...
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Link prediction using deep autoencoder-like non-negative matrix factorization with L21-norm
Link prediction aims to predict missing links or eliminate spurious links and anticipate new links by analyzing observed network topological...
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Neighboring relation enhanced inductive knowledge graph link prediction via meta-learning
Inductive link prediction over knowledge graphs(KGs) aims to perform inference over a new graph with unseen entities. In contrast to transductive...
