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 environment and achieving promising results.
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Nguyen, NV., Tran, MV., Nguyen, HC., Ha, QT. (2021). A Word + Character Embedding Based Relation Extraction Frame for Domain Ontology of Natural Resources and Environment. In: Kim, H., Kim, K.J., Park, S. (eds) Information Science and Applications. Lecture Notes in Electrical Engineering, vol 739. Springer, Singapore. https://doi.org/10.1007/978-981-33-6385-4_11
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DOI: https://doi.org/10.1007/978-981-33-6385-4_11
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