汉语分词与词性标注结合系统的研究

Qin Li, Wei Wei
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引用次数: 2

摘要

本文采用基于词典和统计的方法,构建了一个汉语分词和词性标注相结合的系统。在早期,通过搜索词字典对许多节点进行粗略分割,并生成可能的路径作为候选,而不是选择n条最短路径。在下一阶段,上面生成的每条路径都有一个代价,这个代价是用统计方法计算的。通过提高组合模糊度的精度,选择代价最低的最优路径作为最终结果。初步实验表明,基于混合方法的联合系统的分割精度为94.06%,词性标注精度为90.96%,召回率和F-measure分别在96.86% ~ 95.44.0%和93.67% ~ 92.29%之间。改进系统性能的工作仍在进行中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the System of Jointing Chinese Word Segmentation with Part-of-Speech Tagging
In this paper, we construct a system integrating Chinese word segmentation with part-of-speech tagging, by an approach based dictionary and statistics. In the early stage, many nodes are roughly segmented through searching word dictionary and used to generate possible paths as candidates, instead of choosing N-shortest paths. In the next stage, each path generated above has a cost, which is calculated by a statistical method. With improving the precision of combinational ambiguity, the optimum path that has lowest cost is chosen as the final result. The preliminary experiments show that the segmentation precision of the joint system based on hybrid approach is 94.06%, POS tagging precision 90.96%, and the recall and F-measure range from 96.86% to 95.44.0% and from 93.67% to 92.29% respectively. The Work of improving the performance of the system is still ongoing.
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