<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper explores the linguistic features of ancient and modern Chinese, focuses on capturing the knowledge of the relevant domains of ancient and contemporary Chinese using semantic models, and carries out the corresponding semantic resource extraction and semantic representation through the resource expression mechanism in the framework of the Semantic Association Network Model (SANM), and then analyzes the historical evolution of the lexicalization patterns of the Chinese language and the linguistic features of the Chinese language in different periods. In the historical evolution of Chinese lexicalization patterns, it is found that the distribution of lexicalization patterns of ancient Chinese table-cutting action lexical items is [action+object] > [action+method] > [action result] > [action+tool], and the distribution of lexicalization patterns of modern Chinese table-cutting action lexical items is [action+method] > [action+tool] > [action+result] > [action+object]. The linguistic features of different periods show that all networks have small-world properties and scale-free properties, and the statistical parameters of the networks in each period are relatively close to each other, with the modern network having the most significant C (8.59) and the smallest L (0.92) and γ (0.40). Ancient and modern Chinese words and phrases with relational word collocations in the interval [0,23] have the most extensive and densest distribution of relational words. These data present the similarities and differences between linguistic features between ancient and modern Chinese, which is significant for studying ancient and modern Chinese.</p>
</abstract>

This paper explores the linguistic features of ancient and modern Chinese, focuses on capturing the knowledge of the relevant domains of ancient and contemporary Chinese using semantic models, and carries out the corresponding semantic resource extraction and semantic representation through the resource expression mechanism in the framework of the Semantic Association Network Model (SANM), and then analyzes the historical evolution of the lexicalization patterns of the Chinese language and the linguistic features of the Chinese language in different periods. In the historical evolution of Chinese lexicalization patterns, it is found that the distribution of lexicalization patterns of ancient Chinese table-cutting action lexical items is [action+object] > [action+method] > [action result] > [action+tool], and the distribution of lexicalization patterns of modern Chinese table-cutting action lexical items is [action+method] > [action+tool] > [action+result] > [action+object]. The linguistic features of different periods show that all networks have small-world properties and scale-free properties, and the statistical parameters of the networks in each period are relatively close to each other, with the modern network having the most significant C (8.59) and the smallest L (0.92) and γ (0.40). Ancient and modern Chinese words and phrases with relational word collocations in the interval [0,23] have the most extensive and densest distribution of relational words. These data present the similarities and differences between linguistic features between ancient and modern Chinese, which is significant for studying ancient and modern Chinese.

Lexical Characterization of Ancient and Modern Chinese Combined with Semantic Association Network Modeling

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper explores the linguistic features of ancient and modern Chinese, focuses on capturing the knowledge of the relevant domains of ancient and...

Lexical Characterization of Ancient and Modern Chinese Combined with Semantic Association Network Modeling

Published Online: May 03, 2024

Page range: -

Received: Apr 16, 2024

Accepted: Apr 21, 2024

DOI: https://doi.org/10.2478/amns-2024-0899

Keywords
Semantic modeling, Semantic association network, Ancient and modern Chinese, Lexical features

© 2024 Lixia Zhang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Lexical Characterization of Ancient and Modern Chinese Combined with Semantic Association Network Modeling

Published Online: May 03, 2024

Page range: -

Received: Apr 16, 2024

Accepted: Apr 21, 2024

DOI: https://doi.org/10.2478/amns-2024-0899

KeywordsSemantic modeling, Semantic association network, Ancient and modern Chinese, Lexical features

© 2024 Lixia Zhang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Semantic modeling, Semantic association network, Ancient and modern Chinese, Lexical features