AdaSim
Author:
Affiliation:
1. Hanyang University, Seoul, Republic of Korea
Funder
National Research Foundation of Korea (NRF)
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3459637.3482316
Reference42 articles.
1. Friends and neighbors on the Web
2. Adversarial Training Methods for Network Embedding
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1. Random-Walk-Based or Similarity-Based Methods, Which is Better for Directed Graph Embedding?;2024 IEEE International Conference on Big Data and Smart Computing (BigComp);2024-02-18
2. ELTRA: An Embedding Method based on Learning-to-Rank to Preserve Asymmetric Information in Directed Graphs;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21
3. RealGraph+: A High-Performance Single-Machine-Based Graph Engine that Utilizes IO Bandwidth Effectively;Companion Proceedings of the ACM Web Conference 2023;2023-04-30
4. GELTOR: A Graph Embedding Method based on Listwise Learning to Rank;Proceedings of the ACM Web Conference 2023;2023-04-30
5. Scalable Summarization for Knowledge Graphs with Controlled Utility Loss;Lecture Notes in Computer Science;2023
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