Results 31 to 40 of about 7,799,039 (309)
Temporal Link Prediction: A Unified Framework, Taxonomy, and Review [PDF]
ACM Computing Surveys, 2022 Dynamic graphs serve as a generic abstraction and description of the evolutionary behaviors of various complex systems (e.g., social networks and communication networks).
Meng Qin, Dit-Yan Yeung
semanticscholar +1 more source
Modularity-Aware Graph Autoencoders for Joint Community Detection and Link Prediction [PDF]
Neural Networks, 2022 Graph autoencoders (GAE) and variational graph autoencoders (VGAE) emerged as powerful methods for link prediction. Their performances are less impressive on community detection problems where, according to recent and concurring experimental evaluations,
Guillaume Salha-Galvan +4 more
semanticscholar +1 more source
A Survey on Knowledge Graph Embeddings for Link Prediction
Symmetry, 2021 Knowledge graphs (KGs) have been widely used in the field of artificial intelligence, such as in information retrieval, natural language processing, recommendation systems, etc.
Meihong Wang, Linling Qiu, Xiaoli Wang
semanticscholar +1 more source
Link Prediction in Directed Networks Utilizing the Role of Reciprocal Links
IEEE Access, 2020 Link prediction in directed networks has always been a hot topic in many fields including network science, information system and data mining. Intuitively, once links are endowed with certain orientations, their reciprocate nature can potentially provide
Jinsong Li +5 more
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Graph Neural Networks for Link Prediction
The Florida AI Research Society, 2023 Graph Neural Networks (GNNs) belong to a class of deep learning methods that are specialized for extracting critical information and making accurate predictions on graph representations.
A. Lazar
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Evaluating link prediction methods [PDF]
Knowledge and Information Systems, 2014 Link prediction is a popular research area with important applications in a variety of disciplines, including biology, social science, security, and medicine. The fundamental requirement of link prediction is the accurate and effective prediction of new links in networks.
Yang, Yang +2 more
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Knowledge Graph Embedding for Link Prediction [PDF]
ACM Transactions on Knowledge Discovery from Data, 2020 Knowledge Graphs (KGs) have found many applications in industrial and in academic settings, which in turn, have motivated considerable research efforts towards large-scale information extraction from a variety of sources. Despite such efforts, it is well
Andrea Rossi +4 more
semanticscholar +1 more source
Link prediction method based on complex network dynamics model
网络与信息安全学报, 2019 Link prediction is an important part of the study of missing links and future formations in complex networks.Currently,network structure-based link prediction methods are rich in results.Research on link prediction based on complex network dynamics model
Yonghao PAN, Hongtao YU, Yiteng WU
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A Systematic Analysis of Link Prediction in Complex Network
IEEE Access, 2021 Link mining is an important task in the field of data mining and has numerous applications in informal community. Suppose a real-world complex network, the responsibility of this function is to anticipate those links which are not occurred yet in the ...
Haji Gul +3 more
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Negative Link Prediction in Social Media [PDF]
, 2014 Signed network analysis has attracted increasing attention in recent years. This is in part because research on signed network analysis suggests that negative links have added value in the analytical process.
Belkin M. +6 more
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