Text information extraction is an important method of processing large quantity of text. The application of hidden Markov model to information extraction is a relatively new research topic.
文本信息抽取是处理海量文本的重要手段，将隐马尔可夫模型应用到信息抽取领域是一个比较新的研究课题。
The generic model and basic characteristics of information hidden technology are introduced in this paper, several typical algorithms for the technology are analyzed and compared emphatically.
文章主要介绍了信息隐藏技术的通用模型、特征，重点对现有几种典型算法进行了分析比较。
A new algorithm based on hidden Markov Model is proposed for text information extraction.
提出了一种基于隐马尔可夫模型的文本信息抽取算法。
This paper proposes a new algorithm using hidden Markov model for information extraction based on multiple templates due to the variety of training data.
针对训练数据来源的多样化，提出了基于多模板隐马尔可夫模型的文本信息抽取算法。
The algorithm makes use of the information of format and list separators to segment text, and then combines hidden Markov model for text information extraction.
该算法利用文本排版格式、分隔符等信息，对文本进行分块，在分块的基础上结合隐马尔可夫模型进行文本信息抽取。
We used the regression model of data mining to discover temperature related information hidden in the HIFU focal area subtraction ultrasound images.
该文采用数据挖掘中的回归分析模型，挖掘HIFU焦域处超声剪影图像中可用于温度估计的信息。
In this paper, a parallel sub-state hidden Markov model, which integrates the clean speech and noise information, and each state of the model has several parallel sub-states, is presented.
提出了一种平行子状态隐马尔可夫模型用作噪声鲁棒语音识别的声学模型。
In this paper, a parallel sub-state hidden Markov model, which integrates the clean speech and noise information, and each state of the model has several parallel sub-states, is presented.
提出了一种平行子状态隐马尔可夫模型用作噪声鲁棒语音识别的声学模型。
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