%0 Conference Paper
%A Nguyen, Ngoc Vu
%A Tran, Mai Vu
%A Nguyen, Hai Chau
%A Ha, Quang Thuy
%A Trường Đại học Công nghệ, ĐHQGHN,
%A Cục CNTT, Bộ Tài nguyên và Mội trường,
%B 11th International Conference on Information Science and Applications 2020 (ICISA2020)
%C Virtual Conference
%D 2020
%F SisLab:4175
%T A Word + Character Embedding based Relation Extraction Frame for Domain Ontology of Natural Resources and Environment
%U https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4175/
%X Building domain ontology is a challenging problem, and there are many different approaches for domain ontology construction. However, most of these approaches are still mainly using manual methods [1]. Ontology enrichment is a fairly standard approach in domain ontology construction, in which semi-automated methods and automated methods of ontology learning from a derived ontology. Relation extraction is one of the ways for ontology enrichment. Relation extraction techniques include law-based techniques, machine learning-based techniques with three typical methods: supervised learning, semi-supervised learning, and unsupervised learning. This paper proposes a word + character embedding-based relation extraction frame for the Vietnamese domain ontology of natural resources and environment. The model's effect was demonstrated by experiments in the domain of natural resources and the envi-ronment and achieving promising results.