Study of automatic semantic errors checking for Chinese text based on SKCC

Author

Guan Jun ; Zhang Yang-sen

Author_Institution

Inst. of Intell. Inf. Process., Beijing Inf. Sci. & Technol. Univ., Beijing, China

fYear

2012

fDate

29-31 May 2012

Firstpage

2983

Lastpage

2986

Abstract

This paper focuses on the semantic collocation errors of Chinese text. Based on study of the related properties of “The Semantic Knowledge-base of Modern Chinese (SKCC/SKMC)”, I put forward a method to use semantic classification for automatic error-detection. This paper mainly introduces the method of constructing semantic knowledge base, and the text automatic error-detection algorithm based on this knowledge base. The experimental results show, this method has good experimental results and application prospects.

Keywords

classification; knowledge based systems; natural language processing; text analysis; Chinese text; SKCC; automatic semantic errors checking; semantic classification; semantic collocation error; semantic knowledge base of modern Chinese; text automatic error-detection algorithm; Algorithm design and analysis; Classification algorithms; Educational institutions; Error analysis; Information processing; Knowledge based systems; Semantics; error-detection algorithm; semantic classification; semantic collocation errors; semantic knowledge base;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on

Conference_Location

Sichuan

Print_ISBN

978-1-4673-0025-4

Type

conf

DOI

10.1109/FSKD.2012.6233926

Filename

6233926