Data Analysis Deep Learning Research on Spatiotemporal Preposition Construction Network

Abstract

Chinese space-time prepositions (CSTPs) are a class of function words used to introduce space-time relations into motion or state, which have experienced the process of evolution from ancient Chinese. In recent years, the research on modern CTSPs shows the trend of grammaticalization research, cognitive semantic research, and research based on constructionalization and lexicalization. At present, there are few studies on the systematic semantic description of CTSPs in cognitive linguistics, and their semantic extension is closely related to the cognitive mechanism. This study is aimed at describing and explaining the functions of CSTPs in constructional networks, aiming to provide clearer semantic information for nonnative language learners. This is a comprehensive study combining qualitative and quantitative analysis. Qualitative analysis includes exploration of cognitive mechanisms, description of semantic networks, misinterpretation, and establishment of lexicographically definition model. Quantitative analysis includes data analysis of the Chinese corpus. The importance of qualitative analysis is far greater than that of quantitative analysis. It does not mean that quantitative analysis is not important. Quantitative analysis is important, and qualitative analysis is relatively more important.