分析、设计和实现了一个基于条件随机场模型的汉语分词和词性标注模块。
We analyzed, designed and achieved a module of Chinese word segmentation and Part-Of-Speech Tagging based on Condition Random Fields model.
根据条件随机场模型和马尔可夫随机场模型建立了一个最大后验概率框架。
Firstly, maximum a posteriori framework is created according to conditional random field model and Markov random field model.
针对旅游领域，提出了一种基于层叠条件随机场模型的旅游领域命名实体识别方法。
This paper presents a method for named entity recognition in the tourism domain based on the cascaded conditional random fields.
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