NeuralKG-ind: A Python Library for Inductive Knowledge Graph Representation Learning-Reference-Cited by-同舟云学术

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NeuralKG-ind: A Python Library for Inductive Knowledge Graph Representation Learning

Published:2023-07-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Zhang Wen¹^ORCID,Yao Zhen¹^ORCID,Chen Mingyang²^ORCID,Huang Zhiwei¹^ORCID,Chen Huajun²^ORCID

Affiliation:

1. Zhejiang University, Ningbo, China

2. Zhejiang University, Hangzhou, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3539618.3591809

Reference46 articles.

1. PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings;Ali Mehdi;Journal of Machine Learning Research,2021

2. Freebase

3. Antoine Bordes Nicolas Usunier Alberto Garcia-Duran Jason Weston and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi-relational data. In Advances in neural information processing systems. 2787--2795. Antoine Bordes Nicolas Usunier Alberto Garcia-Duran Jason Weston and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi-relational data. In Advances in neural information processing systems. 2787--2795.

4. Armand Boschin . 2020 . TorchKGE: Knowledge Graph Embedding in Python and PyTorch. In International Workshop on Knowledge Graph: Mining Knowledge Graph for Deep Insights. Armand Boschin. 2020. TorchKGE: Knowledge Graph Embedding in Python and PyTorch. In International Workshop on Knowledge Graph: Mining Knowledge Graph for Deep Insights.

5. LibKGE - A knowledge graph embedding library for reproducible research

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