http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : ( Lua Kim Teng ) (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
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Predication of Meaning of Bisyllabic Chinese Compound Words Using Back Propagation Neural Network
( Lua Kim Teng ) 한국언어정보학회 1995 국제 워크샵 Vol.1995 No.-
A three layer back propagation neural net is set up to study the functional dependency between the semantic class of a bisyllabic Chinese word and that of its two constituent Chinese characters. Simulations were performed using a three-layer back-propagation neural net with various combination of inputs. The inputs are (1) semantic classes of the constituent characters, (2) Entropy of the characters and (3) semantic strength! 1 ] of the characters. Our simulations show that we can obtain the meaning class of a bisyllabic word from the meaning classes of its two constituent characters to an accuracy of 81% by taking the semantic classes and semantic strength of the characters as input. This research establishes the dependency between the meaning class of a Chinese compound word and that of its two constituent characters.
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Neural Networks in Chinese Lexical Classification
( Md Maruf Hasan ),( Kim Teng Lua ) 한국언어정보학회 1996 국제 워크샵 Vol.1996 No.-
Lexical attributes, like syntactic (part-of-speech) and semantic (semantic category) attributes, are in most cases, ambiguous in every languages. Automatic resolution of ambiguity of these attributes can be achieved using`` different techniques; rule-based, statistical, NN-based and their hybrids. Moreover, one linguistic feature also has influence over the resolution of ambiguity of another feature; eg.. knowledge of syntactical category can assist smooth disambiguation of semantic category and vice versa. Properly disambiguated syntactic and semantic properties of lexicon may significantly help us in word sense disambiguation, text analysis, information retreival, natural language understanding and speech processing etc. In this paper, we have presented our neural network based Classification Tool. We have used this tool in Part-of-Speech tagging and Semantic-Category tagging of Chinese lexicon with the help of thesaurus and large training corpus. Experimental results are analysed and compared.
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