Predicting the top-level ontological concepts of domain entities using word embeddings, informal definitions, and deep learning

作者：

Highlights：

• Word embedding and deep learning can be used to predict top-level ontology classes.

• The polysemy of word vectors can be solved by using informal definitions of the word.

• Combining different neural network models have better performance than a single one.

摘要

•Word embedding and deep learning can be used to predict top-level ontology classes.•The polysemy of word vectors can be solved by using informal definitions of the word.•Combining different neural network models have better performance than a single one.

论文关键词：Ontology learning,Deep learning,Well-founded ontology

论文评审过程：Received 27 October 2021, Revised 20 April 2022, Accepted 22 April 2022, Available online 6 May 2022, Version of Record 13 May 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117291