本文提出了一种基于启发式错误驱动学习的中文时间表达式识别的新方法。
This paper proposes a new method for recognizing Chinese time expression based on the heuristic error-driven learning.
本文所研究的时间表达式识别，就是命名实体识别领域一项基础而重要的任务。
In this dissertation, it will focus on time expression recognition, which is one of the most important directions within named entity recognition research area.
时间表达式识别技术主要分为两类：基于机器学习的序列标注方法和基于规则的方法。
There are two main technologies in time expression recognition:sequence labeling method based on machine learning theory and rule-based method.
时间表达式识别是进行时间表达式归一化的基础，其识别结果的好坏直接影响归一化的效果。
Recognizing time expressions is the foundation of its normalization, and its performance directly influences the robustness of the normalization.
时间表达式识别是进行时间表达式归一化的基础，其识别结果的好坏直接影响归一化的效果。
Recognizing time expressions is the foundation of its normalization, and its performance directly influences the robustness of the normalization.
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