Affiliations: [a] School of Automation, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China. E-mail: [email protected] | [b] School of Computer Science, Wuhan University, 39 Luoyu Road, Wuhan 430079, China. E-mail: [email protected] | [c] Shanghai Key Laboratory of Aerospace Intelligent Control Technology, Shanghai Institute of Spaceflight Control Technology, Shanghai 201109, China. E-mail: [email protected] | [d] International School of Software, Wuhan University, 39 Luoyu Road, Wuhan 430079, China
Abstract: Domain terminology recognition and extraction is the primary work for the construction of domain knowledge graph. Traditional method is tedious, and time-consuming, as well as low accuracy. This paper presents an improved Domain Term Extraction-Improvement (TDE-I) method based on relative co-occurrence rate, which can automatically extract domain basic terminologies and domain compound terminologies. We also present a Document Classification Value (DCV) method on the basis of calculating Domain Feature Vector (DFV) value which can implement a judgment to evaluate extraction accuracy according to the evaluation indexes. Our experimental results demonstrate that our approach is effectiveness and accuracy. The proposed method can provide with a new solution for the construction of domain knowledge graph and its applications.