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A Khmer NER method based on conditional random fields fusing with Khmer Entity Characteristics Constraints

机译:基于Khmer实体特征约束的条件随机字段的Khmer ner方法

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摘要

In order to improve the performance of Khmer named entity recognition (NER), a NER method based on conditional random field (CRF) model fusing with Khmer entity characteristics constraints is proposed in this paper. First of all, we carried out analyses on the Khmer entity characteristics, summarized the constraint on these entity characteristics and introduced into the CRF; then solved the labeling sequence by integer linear programming integrated entity characteristic constraint and obtained a model of CRF integrated with constraints based on Khmer entity characteristics. Based on a contrastive experiment, CRF model of the constraint has a better performance than traditional CRF model when carrying out the Khmer NER.
机译:为了提高Khmer命名实体识别(ner)的性能,本文提出了一种基于条件随机场(CRF)模型的NER方法,其中提出了具有Khmer实体特征约束的融合。首先,我们对高棉实体特征进行了分析,总结了这些实体特征的约束并引入CRF;然后通过整数线性编程集成实体特征约束来解决标记序列,并获得基于Khmer实体特征的约束的CRF模型。基于对比实验,约束的CRF模型比传统CRF模型进行了更好的性能,在进行高棉行程时。

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