At first, the text is segmented to words and converted to a sequence of part-of-speech tags; then based on the POS tags sequence parameters and phrase-break distance information from training, Markov model is used to get the most likely phrase break seque
At first, the text is segmented to words and converted to a sequence of part-of-speech tags; then based on the POS tags sequence parameters and phrase-break distance information from training, Markov model is used to get the most likely phrase break seque
首先，文本进行分词，并转换为一列由词性标记所组成的序列；然后使用马尔可夫模型，利用人工标注数据库训练词语连接处词性标注序列的概率分布和连接类型序列的距离信息，得到输入的词性标记序列对应的具有最大似然概率的连接类型序列，最后利用后处理规则进行适当的纠错。