ReliK: A Reliability Measure for Knowledge Graph Embeddings-Reference-Cited by-同舟云学术

ReliK: A Reliability Measure for Knowledge Graph Embeddings

Published:2024-05-13 Issue: Volume:1215 Page:2009-2019
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Container-title:Proceedings of the ACM Web Conference 2024
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Author:

Egger Maximilian K.¹^ORCID,Ma Wenyue¹^ORCID,Mottin Davide¹^ORCID,Karras Panagiotis²^ORCID,Bordino Ilaria³^ORCID,Gullo Francesco³^ORCID,Anagnostopoulos Aris⁴^ORCID

Affiliation:

1. Aarhus University, Aarhus, Denmark

2. U. of Copenhagen & Aarhus U., Copenhagen, Denmark

3. UniCredit, Rome, European Union

4. Sapienza University of Rome, Rome, Italy

Funder

Horizon Europe and Innovation Fund Denmark

PNRR MUR

MUR PRIN

Danish Council for Independent Research

China Scholarship Council

EC H2020RIA

European Commission - NextGenerationEU

ERC Advanced Grant

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589334.3645430

Reference52 articles.

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2. Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models under a Unified Framework

3. Yushi Bai Xin Lv Juanzi Li and Lei Hou. 2023. Answering Complex Logical Queries on Knowledge Graphs via Query Computation Tree Optimization. (2023).

4. Ivana Balazevic Carl Allen and Timothy Hospedales. 2019. TuckER: Tensor Factorization for Knowledge Graph Completion. In 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing. Association for Computational Linguistics 5184--5193.

5. Satadisha Saha Bhowmick Eduard C. Dragut and Weiyi Meng. 2023. Globally Aware Contextual Embeddings for Named Entity Recognition in Social Media Streams. In ICDE. 1544--1557.