Knowledge Graph Error Detection with Hierarchical Path Structure-Reference-Cited by-同舟云学术

Knowledge Graph Error Detection with Hierarchical Path Structure

Published:2023-10-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
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Author:

Zhang Zhao¹^ORCID,Zhang Fuwei¹^ORCID,Zhuang Fuzhen²^ORCID,Xu Yongjun¹^ORCID

Affiliation:

1. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

2. Institute of Artificial Intelligence, Beihang University, Beijing, China

Funder

China Postdoctoral Science Foundation

National Key Research and Development Program of China

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583780.3615201

Reference30 articles.

1. Mining association rules between sets of items in large databases

2. What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization

3. Freebase

4. Antoine Bordes , Nicolas Usunier , Alberto Garcia-Duran , Jason Weston , and Oksana Yakhnenko . 2013. Translating embeddings for modeling multi-relational data. Advances in neural information processing systems , Vol. 26 ( 2013 ). Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi-relational data. Advances in neural information processing systems , Vol. 26 (2013).

5. Convolutional 2D Knowledge Graph Embeddings

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