Encoding and ranking similar Chinese characters

Publication Type:
Journal Article
Citation:
Journal of Information Science and Engineering, 2017, 33 (5), pp. 1195 - 1211
Issue Date:
2017-09-01
Full metadata record
Files in This Item:
Filename Description Size
2f26750d8814fd5edfa770c1e354a15fbd7e.pdfPublished Version4.79 MB
Adobe PDF
© 2017 Institute of Information Science. All Rights Reserved. Automatically detecting similar Chinese characters is useful in many areas, such as building intelligent authoring tools (e.g. automatic multiple choice question generation) in the area of computer assisted language learning. Previous work on the computation of Chinese character similarity focused on detecting character glyph similarity while ignored the importance of other character features, such as pronunciation and meaning. In this article, we present a way to encoding 4,500 simplified Chinese characters in terms of character glyph, pronunciation and meaning, annotating similar Chinese characters and automatically ranking similar characters based on the approach of learning to rank. The experiment results indicated that this approach could be useful for ranking and recognizing similar Chinese characters in terms of glyph, pinyin and semantic meaning. Moreover, it has been found that the learning to rank Listwise (ListNet) method was more effective than Pointwise (MART) and Pairwise (RankNet).
Please use this identifier to cite or link to this item: