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篇名
Enhancement of Feature Engineering for Conditional Random Field Learning in Chinese Word Segmentation Using Unlabeled Data
作者 Mike Tian-Jian Jiang (Mike Tian-Jian Jiang)Cheng-Wei Shih (Cheng-Wei Shih)Ting-Hao Yang (Ting-Hao Yang)Chan-Hung Kuo (Chan-Hung Kuo)Richard Tzong-Han Tsai (Richard Tzong-Han Tsai)Wen-Lian Hsu (Wen-Lian Hsu)
中文摘要
This work proposes a unified view of several features based on frequent strings extracted from unlabeled data that improve the conditional random fields (CRF) model for Chinese word segmentation (CWS). These features include character-based n-gram (CNG), accessor variety based string (AVS) and its variation of left-right co-existed feature (LRAVS), term-contributed frequency (TCF), and term-contributed boundary (TCB) with a specific manner of boundary overlapping. For the experiments, the baseline is the 6-tag, a state-of-the-art labeling scheme of CRF-based CWS, and the data set is acquired from the 2005 CWS Bakeoff of Special Interest Group on Chinese Language Processing (SIGHAN) of the Association for Computational Linguistics (ACL) and SIGHAN CWS Bakeoff 2010. The experimental results show that all of these features improve the performance of the baseline system in terms of recall, precision, and their harmonic average as F1 measure score, on both accuracy (F) and out-of-vocabulary recognition (FOOV). In particular, this work presents compound features involving LRAVS/AVS and TCF/TCB that are competitive with other types of features for CRF-based CWS in terms of F and FOOV, respectively.
起訖頁 45-85
關鍵詞 Conditional Random FieldsWord SegmentationAccessor VarietyTerm-contributed FrequencyTerm-contributed Boundary
刊名 中文計算語言學期刊  
期數 201209 (17:3期)
出版單位 中華民國計算語言學學會
該期刊-上一篇 聲符部件排序與形聲字發音規則探勘
該期刊-下一篇 Strategies of Processing Japanese Names and Character Variants in Traditional Chinese Text
 

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