@inproceedings{SisLab4175,
       booktitle = {11th International Conference on Information Science and Applications 2020 (ICISA2020)},
           month = {December},
           title = {A Word + Character Embedding based Relation Extraction Frame for Domain Ontology of Natural Resources and Environment},
          author = {Ngoc Vu Nguyen and Mai Vu Tran and Hai Chau Nguyen and Quang Thuy Ha},
            year = {2020},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4175/},
        abstract = {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.}
}