首页|Findings from School of Geosciences and Info-Physics in the Area of Machine Learning Described (A Hybrid Method of Combination Probability and Machine Learning for Chinese Geological Text Segmentation)
Findings from School of Geosciences and Info-Physics in the Area of Machine Learning Described (A Hybrid Method of Combination Probability and Machine Learning for Chinese Geological Text Segmentation)
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NETL
NSTL
Elsevier
Research findings on Machine Learning are discussed in a new report. According to news reporting from Changsha, People’s Republic of China, by NewsRx journalists, research stated, “To address the issues surrounding incomplete coverage of core dictionaries, limited training corpora, and low precision in Chinese geological text segmentation, a knowledge-and data-driven word segmentation method by combining combination probability and machine learning was proposed in this paper. We extracted mathe-matical feature information from terms in Chinese geological text to construct a Term Combination Probability Model (TCPM) for Chinese word combinations by integrating the combination features of geological terms and the Chinese writing styles under zero-sample conditions.” Financial support for this research came from National Natural Science Foundation of China (NSFC). The news correspondents obtained a quote from the research from the School of Geosciences and Info-Physics, “The TCPM was used to extract geological terms with high combination characteristics as a user-defined dictionary, and then a geological corpus was constructed by using a general domain word segmentation method based on this dictionary. After a small amount of manual review and optimization, the geological corpus was trained with a BiLSTM-CRF model to segment Chinese geological text. The proposed method in this paper was tested using a regional geological survey report set in Henan Province, and the precision, recall, and F1-score of the method are 92.65%, 92.53%, and 92.59%, respectively.”
ChangshaPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningSchool of Geosciences and Info-Physics
NETL
NSTL
Elsevier
