NEW: A generic learning model for tie strength prediction in networks-Reference-Cited by-同舟云学术

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NEW: A generic learning model for tie strength prediction in networks

Published:2020-09 Issue: Volume:406 Page:282-292
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Liu Zhen^ORCID,Li Hu,Wang Chao^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference34 articles.

1. Growing closer on facebook: changes in tie strength through social network site use;Burke,2014

2. Empirical analysis of an evolving social network;Kossinets;science,2006

3. The strength of weak ties;Granovetter,1977

4. Predicting tie strength with social media;Gilbert,2009

5. Measuring tie strength;Marsden;Social forces,1984

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1. Self-Attention Enhanced Auto-Encoder for Link Weight Prediction With Graph Compression;IEEE Transactions on Network Science and Engineering;2024-01

2. Cone: A Common Neighbor-Aware Link Weight Prediction Method with Simplified Graph Transformer;2024

3. RGSE: Robust Graph Structure Embedding for Anomalous Link Detection;IEEE Transactions on Big Data;2023-10

4. Link and edge weight prediction in air transport networks — An RNN approach;Physica A: Statistical Mechanics and its Applications;2023-03

5. Link Weight Prediction in Directed Networks Based on Graph Convolution Network;2022 8th International Conference on Big Data and Information Analytics (BigDIA);2022-08-24

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