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A Khmer NER method based on conditional random fields fusing with Khmer entity characteristics constraints

机译：基于条件随机场与高棉实体特征约束融合的高棉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：为了提高高棉命名实体识别（NER）的性能，提出了一种基于条件随机场（CRF）模型融合高棉实体特征约束的NER方法。首先，我们对高棉实体特征进行了分析，总结了对这些实体特征的约束，并将其引入了CRF;然后通过整数线性规划综合实体特征约束条件求解标注序列，得到基于高棉实体特征约束条件的CRF模型。基于对比实验，在进行高棉NER时，约束的CRF模型具有比传统CRF模型更好的性能。

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