頁籤選單縮合
題 名 | Unknown Word Detection for Chinese by a Corpus-based Learning Method |
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作 者 | Chen,Keh-jiann; Bai,Ming-hong; | 書刊名 | International Journal of Computational Linguistics & Chinese Language Processing |
卷 期 | 3:1 1998.02[民87.02] |
頁 次 | 頁27-44 |
分類號 | 312.23 |
關鍵詞 | |
語 文 | 英文(English) |
英文摘要 | One of the most prominent problems in computer processing of the Chinese language is identification of the words in a sentence. Since there are no blanks to mark word boundaries, identifying words is difficult because of segmentation ambiguities and occurrences of out-of-vocabulary words (i.e., unknown words). In this paper, a corpus-based learning method is proposed which derives sets of syntactic rules that are applied to distinguish monosyllabic words from monosyllabic morphemes which may be parts of unknown words or typographical errors. The corpus-based learning approach has the advantages of: 1. automatic rule learning, 2. automatic evaluation of the performance of each rule, and 3. balancing of recall and precision rates through dynamic rule set selection. The experimental results show that the rule set derived using the proposed method outperformed hand-crafted rules produced by human experts in detecting unknown words. |
本系統中英文摘要資訊取自各篇刊載內容。