Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/60449
Title: Sense prediction study : two corpus-driven linguistic approaches
Authors: Hong, JF
Ker, SJ
Ahrens, K
Huang, C 
Keywords: Lexical ambiguity
Sense prediction
Corpus-based approach
Character similarity clustering approach
Concept similarity clustering approach
Evaluation
Issue Date: 2011
Publisher: World Scientific
Source: International journal of computer processing of languages, 2011, v. 23, no. 3, p. 229-241 How to cite?
Journal: International journal of computer processing of languages 
Abstract: In this study, we propose to use two corpus-driven linguistic approaches for a sense prediction study. We will concentrate on the character similarity clustering approach and the concept similarity clustering approach to predict the senses of non-assigned words by using corpora and tools, such as the Chinese Gigaword Corpus and HowNet. In this study, we will evaluate sense predictions via the sense divisions of Chinese Wordnet (CWN) and Xiandai Hanyu Cidian (Xian Han). Using these corpora, we will determine the clusters of our four target words — chi1 "eat", wan2 "play", huan4 "change", and shao1 "burn" — in order to predict all possible senses and then evaluate them. This process will demonstrate the viability of the corpus-based approaches.
URI: http://hdl.handle.net/10397/60449
ISSN: 1793-8406 (print)
2010-0205 (online)
DOI: 10.1142/S1793840611002322
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