Abstract
The ontology construction process is very expensive and time consuming when performed manually. In order to solve the problems of time consumption and high cost, a Chinese domain ontology learning method based on semantic dependency and formal concept analysis is proposed in this chapter. During the learning process, semantic dependency analysis technology is used for extracting formal context from unstructured domain texts, and Godin algorithm is used for constructing concept lattice. At last, the chapter takes a medical ontology construction as an example to verify this method. The experiment results show that the method we proposed can construct domain ontology automatically and reduce manual intervention. In addition, the ontology we got is a formal ontology, so it has more advantages in sharing and reusability.
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Hou, L., Zheng, S., He, H., Peng, X. (2014). Chinese Domain Ontology Learning Based on Semantic Dependency and Formal Concept Analysis. In: Wong, W.E., Zhu, T. (eds) Computer Engineering and Networking. Lecture Notes in Electrical Engineering, vol 277. Springer, Cham. https://doi.org/10.1007/978-3-319-01766-2_56
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DOI: https://doi.org/10.1007/978-3-319-01766-2_56
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