Can Persistent Homology provide an efficient alternative for Evaluation of Knowledge Graph Completion Methods?

Author:

Bastos Anson1ORCID,Singh Kuldeep2ORCID,Nadgeri Abhishek3ORCID,Hoffart Johannes4ORCID,Singh Manish5ORCID,Suzumura Toyotaro6ORCID

Affiliation:

1. IIT, Hyderabad, India

2. Cerence GmbH and Zerotha Research, Germany

3. RWTH Aachen, Germany

4. SAP, Germany

5. IIT Hyderabad, India

6. The University of Tokyo, Japan

Publisher

ACM

Reference65 articles.

1. Topology Applied to Machine Learning: From Global to Local

2. Mehdi Ali , Max Berrendorf , Charles Tapley Hoyt , Laurent Vermue , Mikhail Galkin , Sahand Sharifzadeh , Asja Fischer , Volker Tresp , and Jens Lehmann . 2021. Bringing light into the dark: A large-scale evaluation of knowledge graph embedding models under a unified framework . IEEE Transactions on Pattern Analysis and Machine Intelligence ( 2021 ). Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Mikhail Galkin, Sahand Sharifzadeh, Asja Fischer, Volker Tresp, and Jens Lehmann. 2021. Bringing light into the dark: A large-scale evaluation of knowledge graph embedding models under a unified framework. IEEE Transactions on Pattern Analysis and Machine Intelligence (2021).

3. TuckER: Tensor Factorization for Knowledge Graph Completion

4. The Impact of Negative Triple Generation Strategies and Anomalies on Knowledge Graph Completion

5. HopfE

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Using Model Calibration to Evaluate Link Prediction in Knowledge Graphs;Proceedings of the ACM Web Conference 2024;2024-05-13

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