Author:
Yu-Ta Chen, Yaw-Huei Chen, and Yu-Chih Cheng
Abstract:
This paper investigates the appropriateness of using lexical cohesion analysis to assess Chinese readability. In addition to term frequency features, we derive features from the result of lexical chaining to capture the lexical cohesive information, where E-HowNet lexical database is used to compute semantic similarity between nouns with high word frequency. Classification models for assessing readability of Chinese text are learned from the features using support vector machines. We select articles from textbooks of elementary schools to train and test the classification models. The experiments compare the prediction results of different sets of features.
Keywords:
Readability, Chinese Text, Lexical Chain, TF-IDF, SVM
Author:
Jia-Fei Hong and Chu-Ren Huang
Abstract:
Studies of cross-strait lexical differences in the use of
Mandarin Chinese reveal that a divergence has become increasingly evident. This
divergence is apparent in phonological, semantic, and pragmatic analyses and has
become an obstacle to knowledge-sharing and information exchange. Given the wide
range of divergences, it seems that Chinese character forms offer the most
reliable regular mapping between cross-strait usage contrasts. In this study, we
take general cross-strait lexical wordforms to discovery of cross-strait lexical
differences and explore their contrasts and variations.
Based on Hong and Huang (2006), we discuss the same conceptual words between cross-strait usages by WordNet, Chinese Concept Dictionary (CCD) and Chinese Wordnet (CWN). In this study, we take all words which appear in CCD and CWN to check their lexical contrasts of traditional Chinese character data and simplified Chinese character data in Gigaword Corpus, explore their appearances and distributions, and compare and demonstrate them via Google website.
Keywords:
CCD, CWN, WordNet, Gigaword Corpus, Google, Cross-Strait Lexical Wordforms, Semantics, Concepts
Author:
F. Y. August Chao and Siaw-Fong Chung
Abstract:
Synonym groups can serve as resourceful linguistic metadata for information extraction and word sense disambiguation. Nevertheless, the reasons two words can be categorized into a particular synonym group need further study, especially when no explanation is available as to why any two words are synonymous. Lexical resources, such as the Chinese Synonym Forest (or Tongyici Cilin) (Mei et al. 1983), assemble lexical items into hierarchical categories via manual categorization. Other than this, statistical measures, such as co-existing probability, have been adopted widely to verify synonymous relationships. Nevertheless, a purely statistical method does not provide description that can help interpret why such a synonymous relationship occurs. We propose a novel method for the study of shared concepts within any synonym group by comparing co-existing words in the dictionary definition of each member in the group. The co-existing words are seen as the representatives of shared concepts that can be used for interpretating any hidden meaning among members of a synonym group. We also compare our results with the thesaurus function in the Sketch Engine (Kilgarriff et al. 2004), which uses statistical data in the form of Sketch scores. The results show that our method can produce concept words according to dictionary definitions, but this method also has its limitations, as it works only with a finite number of synonyms and under limited computing resources.
Keywords:
Shared Concept, Synonym, Chinese Synonym Forest, Dictionary Definition
Author:
Chan-Chia Hsu and Shu-Kai Hsieh
Abstract:
There has been no consensus as to what constitutes a set of base concepts in the mental landscape. With the aim of exploring base concepts in Chinese, this paper proposes that frequently-occurring words in the glosses of a lexical resource such as the Chinese Wordnet can be seen as a candidate set of base concepts because the glosses use basic words. The present study identified 130 base concepts in Chinese. The Base Concepts in EuroWordNet were adopted as a reference for comparison. While only 44.6% of the base concepts identified in the present study have an equivalent in the set of Base Concepts of EuroWordNet, the other base concepts extracted by our gloss-based approach also reflect a certain degree of basicness. It is hoped that both the overlap and the difference between different sets of base concepts identified in different languages and by different approaches can deepen our understanding of the basic core in the mind. Additionally, it is also hoped that the set of base concepts identified in the present study can have computational as well as pedagogical applications in the future.
Keywords:
Chinese Wordnet, EuroWordNet, Base Concept, Gloss