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Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec

, , , , , and . (2017)cite arxiv:1710.02971Comment: 9 pages, published in WSDM 2018 proceedings.
DOI: 10.1145/3159652.3159706

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Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec, , , , , and . (2017)cite arxiv:1710.02971Comment: 9 pages, published in WSDM 2018 proceedings.Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries., , , , , , , , and . KDD, page 1120-1130. ACM, (2022)Pre-Trained Models: Past, Present and Future., , , , , , , , , and 12 other author(s). CoRR, (2021)Pre-trained models: Past, present and future., , , , , , , , , and 14 other author(s). AI Open, (2021)Energy-traffic tradeoff cooperative offloading for mobile cloud computing., , , , and . IWQoS, page 284-289. IEEE, (2014)Approximating Element-Wise Functions of Matrix with Improved Streaming Randomized SVD., , , , and . ICTAI, page 122-130. IEEE, (2022)Modeling and Predicting Learning Behavior in MOOCs., , , , , , and . WSDM, page 93-102. ACM, (2016)Network Embedding as Matrix Factorization, , , , , and . Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining - WSDM \textquotesingle18, ACM Press, (2018)GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training., , , , , , , and . KDD, page 1150-1160. ACM, (2020)Towards Lightweight and Automated Representation Learning System for Networks., , , , , , and . CoRR, (2023)