Results 21 to 30 of about 6,752,678 (299)
Retweets as a Predictor of Relationships among Users on Social Media. [PDF]
PLoS ONE, 2017 Link prediction is the problem of detecting missing links or predicting future link formation in a network. Application of link prediction to social media, such as Twitter and Facebook, is useful both for developing novel services and for sociological ...
Sho Tsugawa, Kosuke Kito
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Review on Learning and Extracting Graph Features for Link Prediction
Machine Learning and Knowledge Extraction, 2020 Link prediction in complex networks has attracted considerable attention from interdisciplinary research communities, due to its ubiquitous applications in biological networks, social networks, transportation networks, telecommunication networks, and ...
Ece C. Mutlu +3 more
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Missing Link Prediction Using Non-Overlapped Features and Multiple Sources of Social Networks
Information, 2021 The current methods for missing link prediction in social networks focus on using data from overlapping users from two social network sources to recommend links between unconnected users. To improve prediction of the missing link, this paper presents the
Pokpong Songmuang +2 more
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Taxonomy of Link Prediction for Social Network Analysis: A Review
IEEE Access, 2020 Link prediction is a technique to forecast future new or missing relationships between entities based on the current network information. Graph theory and network science are theoretical concepts that have influenced the link prediction research ...
Herman Yuliansyah +2 more
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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
Linkless Link Prediction via Relational Distillation [PDF]
International Conference on Machine Learning, 2022 Graph Neural Networks (GNNs) have shown exceptional performance in the task of link prediction. Despite their effectiveness, the high latency brought by non-trivial neighborhood data dependency limits GNNs in practical deployments.
Zhichun Guo +6 more
semanticscholar +1 more source
Classification using link prediction [PDF]
Neurocomputing, 2019 Link prediction in a graph is the problem of detecting the missing links that would be formed in the near future. Using a graph representation of the data, we can convert the problem of classification to the problem of link prediction which aims at finding the missing links between the unlabeled data (unlabeled nodes) and their classes.
Seyed Amin Fadaee, Maryam Amir Haeri
openaire +2 more sources
Multi-scale link prediction [PDF]
Proceedings of the 21st ACM international conference on Information and knowledge management, 2012 20 pages, 10 ...
Shin, Donghyuk +2 more
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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
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