COGNITIVE LINGUISTIC PERSPECTIVES ON THE CHINESE LANGUAGE

Yingxu Wang ()
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Yingxu Wang: International Institute of Cognitive Informatics and Cognitive Computing (𝕀CIℂ), Laboratory for Cognitive Informatics and Cognitive Computing, Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, 2500 University Drive, NW, Calgary, Alberta, Canada T2N 1N4, USA

New Mathematics and Natural Computation (NMNC), 2013, vol. 09, issue 02, 237-260

Abstract: Chinese is one of the oldest and most widely used languages with an ideographic writing system. It is curious to analyze the advantages and disadvantages of Chinese in cognitive linguistics, cognitive informatics, and knowledge science. This paper presents a comparative study on the fundamental theories and formal models of Chinese and other languages. A number of interesting findings on the cognitive and social impacts of the widely used Chinese language are revealed. It is found that, although the idiographic languages are more efficient in language manipulation, the alphabetic languages contributed more to the development of the knowledge processing power of the brain. A set of fundamental properties of knowledge is elicited, which reveals that the knowledge space of an individual is proportional to both the number of concepts and the number of their relations developed in long-term memory of the brain. Toward a more powerful and efficient scientific language for rigorous inference, the expression means of the Chinese language may yet need to be extended in its abstraction mechanisms and a convergent approach to integrate and synergize observations and truths in order to form rigorous theories and a formal knowledge framework. The findings of this work provide a foundation for comparative studies on Chinese and other languages in particular, and for cognitive linguistics and knowledge science in general.

Keywords: Chinese language; linguistic models; formal models; cognitive informatics; cognitive computing; knowledge science; computational linguistics; deductive grammar; formal semantics; denotational mathematics; symbolic inference; cognitive linguistics (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1142/S179300571340005X

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