@inproceedings{2e84ddac23a9490b9aa5a0c32582f063,
title = "Unsupervised Knowledge Graph Generation Using Semantic Similarity Matching",
abstract = "Knowledge Graphs (KGs) are directed labeled graphs representing entities and the relationships between them. Most prior work focuses on supervised or semi-supervised approaches which require large amounts of annotated data. While unsupervised approaches do not need labeled training data, most existing methods either generate too many redundant relations or require manual mapping of the extracted relations to a known schema. To address these limitations, we propose an unsupervised method for KG generation that requires neither labeled data nor manual mapping to the predefined relation schema. Instead, our method leverages sentence-level semantic similarity for automatically generating relations between pairs of entities. Our proposed method outperforms two baseline systems when evaluated over four datasets.",
author = "Lixian Liu and Amin Omidvar and Zongyang Ma and Ameeta Agrawal and Aijun An",
note = "Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 3rd Workshop on Deep Learning Approaches for Low-Resource NLP, DeepLo 2022 ; Conference date: 14-07-2022",
year = "2022",
language = "English",
series = "DeepLo 2022 - 3rd Workshop on Deep Learning Approaches for Low-Resource NLP, Proceedings of the DeepLo Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "169--179",
editor = "Colin Cherry and Angela Fan and George Foster and Gholamreza Haffari and Shahram Khadivi and Nanyun Peng and Xiang Ren and Ehsan Shareghi and Swabha Swayamdipta",
booktitle = "DeepLo 2022 - 3rd Workshop on Deep Learning Approaches for Low-Resource NLP, Proceedings of the DeepLo Workshop",
}