@inproceedings{e7d690c0f3f94e0681caeb109049bb8c,
title = "漢字難度分析暨回饋系統之建置與發展",
abstract = "Feature analysis of Chinese characters plays a prominent role in {"}character-based{"} education. However, there is an urgent need for a text analysis system for processing the difficulty of composing components for characters, primarily based on Chinese learners' performance. To meet this need, the purpose of this research was to provide such a system by adapting a data-driven approach. Based on Chen et al.'s (2011) Chinese Orthography Database, this research has designed and developed an system: Character Difficulty - Research on Multi-features (CD-ROM). This system provides three functions: (1) analyzing a text and providing its difficulty regarding Chinese characters; (2) decomposing characters into components and calculating the frequency of components based on the analyzed text; and (3) affording component-deriving characters based on the analyzed text and downloadable images as teaching materials. With these functions highlighting multi-level features of characters, this system has the potential to benefit the fields of Chinese character instruction, Chinese orthographic learning, and Chinese natural language processing.",
keywords = "character difficulty, character features, character-based education, instructional system for Chinese character education",
author = "Haung, {Jung En} and Tseng, {Hou Chiang} and Chang, {Li Yun} and Chen, {Hsueh Chih} and Sung, {Yao Ting}",
note = "Publisher Copyright: {\textcopyright} 2022 the Association for Computational Linguistics and Chinese Language Processing (ACLCLP).; 34th Conference on Computational Linguistics and Speech Processing, ROCLING 2022 ; Conference date: 21-11-2022 Through 22-11-2022",
year = "2022",
language = "繁體中文",
series = "ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing",
publisher = "The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)",
pages = "256--262",
editor = "Yung-Chun Chang and Yi-Chin Huang and Jheng-Long Wu and Ming-Hsiang Su and Hen-Hsen Huang and Yi-Fen Liu and Lung-Hao Lee and Chin-Hung Chou and Yuan-Fu Liao",
booktitle = "ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing",
}