Accurate Part-of-Speech Tagging via Conditional Random Field

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• 关键词：POS tagging ; CRF ; Part ; of ; Speech ; Conditional random field ; Accurate ; prediction
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：10036
• 期：1
• 页码：217-224
• 丛书名：Internet of Vehicles ?Technologies and Services
• ISBN：978-3-319-51969-2
• 卷排序：10036

文摘

POS tagging (i.e. part-of-speech tagging) is an important component of syntactic parsing in the field of natural language processing. While CRF (i.e. conditional random field) is a class of statistical modelling method often applied in pattern recognition and machine learning, where it is used for structured prediction. As POS tagging can be considered as a structured prediction task to some extent, so in this paper, we proposed to utilize the inherent advantages of CRF, and apply it to POS tagging task to get more accurate. The subsequent experiments are introduced to validate our proposed method.