【摘要】 隐马尔可夫模型是序列数据处理和统计学习的一种重要概率模型,最近几年已经被成功应用到许多关于自然语言处理的任务中。简要介绍了隐马尔可夫模型,对其在词性标注应用中的难点、模型的建立、Viterbi算法等问题进行了详细论述,给出了基于隐马尔可夫模型的中文科研论文头部信息抽取过程以及模型结构的学习和参数的训练等关键问题的解决办法。更多还原

【Abstract】 Hidden markov model is an important probabilistic model to solve sequence representation and statistical problem,and have been applied with success to many natural language-related tasks.First,hidden markov model is simply introduced.Then these difficulties is discussed,building model and Viterbi algorithm in the post-of-speech tagging based on hidden markov model in detail;and the process based on hidden markov model is proposed for extracting the information of paper header and citation from Chinese research papers;and the methods to address learning hidden Markov model structure and parameter estimation are given.更多还原