Considering similar nodes should present closer embedding vectors with network representation learning, in this paper, we propose a Graph ATtention network method based on node Similarity (SiGAT) for link prediction. Specifically, we calculate similar node set for e...
Dynamic network link prediction is extensively applicable in various scenarios, and it has progressively emerged as a focal point in data mining research. The comprehensive and accurate extraction of node information, as well as a deeper understanding of
real-world networks demonstrate that the proposed algorithm has great advantages in the label classification,network reconstruction and link prediction tasks,... S Liu,C Yang,Y Liu - 《Intelligent Automation & Soft Computing》 被引量: 0发表: 2023年 Multi-Scale Variational Graph AutoEncoder for Li...
摘要:知识图谱(Knowledge graph, KGs)在工业和学术领域有很多应用,这反过来又推动了从各种来源大规模提取信息的研究工作。尽管付出了诸多努力,但不得不承认最先进的知识图谱也是不完整的。链路预测(Link Prediction, LP)是一种根据知识图谱中的已存在实体去预测缺失事实的任务,它是一种有前途、广泛研究且旨在解决知识...
[27] Liu, Meng, and Yong Liu. Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences. ACM SIGIR, 2021. [28] Qu, Liang, et al. Continuous-Time Link Prediction via Temporal Dependent Graph Neural Network. ACM WWW, 2020. ...
Inspired by the great success of deep learning frameworks, especially the convolution neural network (CNN) and long short-term memory (LSTM) network, we propose a novel end-to-end model with a Graph Convolution Network(GCN) embedded LSTM, named GC-LSTM, for dynamic network link prediction. ...
We vary the number of γ and the λ to determine their impact on the network link prediction. The Each data point is averaged over 100 independent runs. Full size image As represented in Tables 2, 3 and 4, we show the performance on the ten real world networks with the proportion of ...
Attention-based explainable friend link prediction with heterogeneous context information 2022, Information Sciences Citation Excerpt : Based on user and item interactions, Wang et al. [40] utilized a graph network and suggested a unified collaborative filtering framework for capturing the correlations bet...
We further show that factorization models for link prediction such as DistMult can be significantly improved through the use of an R-GCN encoder model to accumulate evidence over multiple inference steps in the graph, demonstrating a large improvement of 29.8% on FB15k-237 over a decoder-only ...
(2022). Vehicle Trajectory Prediction Based on Graph Attention Network. In: Sun, F., Hu, D., Wermter, S., Yang, L., Liu, H., Fang, B. (eds) Cognitive Systems and Information Processing. ICCSIP 2021. Communications in Computer and Information Science, vol 1515. Springer, Singapore. ...