λ-active learning based microblog-oriented Chinese word segmentation

ZHANG Jing; HUANG Degen; HUANG Kaiyu; LIU Zhuang; MENG Xiangzhu

doi:10.16511/j.cnki.qhdxxb.2018.26.011

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Journal of Tsinghua University(Science and Technology) ›› 2018, Vol. 58 ›› Issue (3) : 260-265. DOI: 10.16511/j.cnki.qhdxxb.2018.26.011

COMPUTER SCIENCE AND TECHNOLOGY

λ-active learning based microblog-oriented Chinese word segmentation

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Abstract

Current manual segmented microblog-oriented corpora are inadequate, so both conventional Chinese word segmentation (CWS) systems and deep learning based CWS systems are still not very effective. This paper presents an active learning method that selects samples with high annotation values from unlabelled tweets for microblog-oriented CWS. A parameter is introduced to control the number of repeatedly selected samples that offen occur in microblog data. Three strategies (Max, Avg and AvgMax) are used to evaluate the overall values of each sample. The initial segment character is a stop character which is calculated by taking character embeddings into consideration. Tests demonstrate that this method outperforms the baseline system with F Gains of 0.84%~1.49% and state-of-the-art active learning method word boundary annotation (WBA).

Key words

word information processing / Chinese word segmentation / active learning / diversity of samples / microblog-oriented data

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ZHANG Jing, HUANG Degen, HUANG Kaiyu, LIU Zhuang, MENG Xiangzhu. λ-active learning based microblog-oriented Chinese word segmentation[J]. Journal of Tsinghua University(Science and Technology). 2018, 58(3): 260-265 https://doi.org/10.16511/j.cnki.qhdxxb.2018.26.011

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