Results 241 to 250 of about 6,752,678 (299)

Community-enhanced Link Prediction in Dynamic Networks

ACM Transactions on the Web, 2023
The growing popularity of online social networks is quite evident nowadays and provides an opportunity to allow researchers in finding solutions for various practical applications.
Mukesh Kumar, S. Mishra, S. Singh, Bhaskar Biswas   +3 more
semanticscholar   +1 more source

Heterogeneous Hypergraph Variational Autoencoder for Link Prediction

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Link prediction aims at inferring missing links or predicting future ones based on the currently observed network. This topic is important for many applications such as social media, bioinformatics and recommendation systems.
Haoyi Fan, Fengbin Zhang, Yuxuan Wei, Zuoyong Li, C. Zou, Yue Gao, Qionghai Dai   +6 more
semanticscholar   +1 more source

Few-shot Link Prediction in Dynamic Networks

Web Search and Data Mining, 2022
Dynamic link prediction, which aims at forecasting future edges of a node in a dynamic network, is an important problem in network science and has a wide range of real-world applications.
Cheng Yang, Chuncheng Wang, Yuanfu Lu, Xumeng Gong, Chuan Shi, Wei Wang, Xu Zhang   +6 more
semanticscholar   +1 more source

Impact of Centrality Measures on the Common Neighbors in Link Prediction for Multiplex Networks

Big Data, 2022
Complex networks are representations of real-world systems that can be better modeled as multiplex networks, where the same nodes develop multi-type connections.
E. Nasiri, K. Berahmand, Zeynab Samei, Yuefeng Li   +3 more
semanticscholar   +1 more source

Generative dynamic link prediction

Chaos: An Interdisciplinary Journal of Nonlinear Science, 2019
In networks, a link prediction task aims at learning potential relations between nodes to predict unknown potential linkage states. At present, most link prediction methods are used to process static networks. These methods cannot produce good prediction results for dynamic networks.
Jinyin Chen, Xiang Lin, Chenyu Jia, Yuwei Li, Yangyang Wu, Haibin Zheng, Yi Liu   +6 more
openaire   +2 more sources

Knowledge Graph Large Language Model (KG-LLM) for Link Prediction

Asian Conference on Machine Learning
The task of multi-hop link prediction within knowledge graphs (KGs) stands as a challenge in the field of knowledge graph analysis, as it requires the model to reason through and understand all intermediate connections before making a prediction. In this
Dong Shu, Tianle Chen, Mingyu Jin, Yiting Zhang, Chong Zhang, Mengnan Du, Yongfeng Zhang   +6 more
semanticscholar   +1 more source

Link prediction techniques, applications, and performance: A survey

, 2020
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; Barabasi and Albert, 1999; Kleinberg, 2000; Leskovec et al.
Ajay Kumar, S. Singh, Kuldeep Singh, Bhaskar Biswas   +3 more
semanticscholar   +1 more source

Link direction for link prediction

Physica A: Statistical Mechanics and its Applications, 2017
Abstract Almost all previous studies on link prediction have focused on using the properties of the network to predict the existence of links between pairs of nodes. Unfortunately, previous methods rarely consider the role of link direction for link prediction.
Ke-ke Shang, Michael Small, Wei-sheng Yan   +2 more
openaire   +1 more source

Predicting the Link Strength of "Newborn" Links

Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion, 2016
Measurements of online social networks (OSNs) support the common fact that not all links carry the same social value, and that the strength of each link is strictly related to the frequency of interactions between the connected users. In this paper, we investigate the predictability of the interactions on OSN links by wondering if it is possible to ...
M. Zignani, S. Gaito, G.P. Rossi
openaire   +1 more source

Building trust/distrust relationships on signed social service network through privacy-aware link prediction process

Applied Soft Computing, 2021
With the ever-increasing popularity of social software, we can easily establish a s igned s ocial n etwork (SSN) by capturing users’ attitudes (i.e., trust/distrust, friend/enemies, consent/opposition) toward other people.
Huaizhen Kou, Hanwen Liu, Yucong Duan, Wenwen Gong, Yanwei Xu, Xiaolong Xu, Lianyong Qi   +6 more
semanticscholar   +1 more source