语言模型

利用语义词典Web挖掘语言模型的无指导译文消歧

Unsupervised Translation Disambiguation by Using Semantic Dictionary and Mining Language Model from Web

基于Web网页语料构建动态语言模型

Updating language model based on training text from Webs

基于PATTREE统计语言模型与关键词自动提取

PAT - TREE Based Language Model and Automatic Keyword Extraction

也就是说，中文统计语言模型和IR相结合有没有前途？

That is to say , Chinese statistical language models combined with IR have future ?

本文进一步研究了如何在语言模型框架下更好地利用passage特征。

This paper further investigates how to utilize the passage feature in the statistic language model framework .

并得出结论：对于基于真实词的汉语N元语言模型，N的取值范围应介于3至6之间，且N＝4为较优。

Finally , a conclusion was obtained that 4 is a better selection of parameter N value for n gram model based on words in Chinese language .

实验表明这种改进在很大程度上提高了原有模型的性能，与n元语言模型相比困惑度下降了401%，有效地增强了语言模型的自适应性。

Experiments have shown that the performance of the adaptive model has been improved greatly and the perplexity has decreased almost 40.1 % compared with n-gram language model .

CSCW环境下多数据库的操作语言模型

Operating Language Model of Multidatabase in CSCW Environment

讨论基于自动机/形式语言模型的离散事件系统（DES）的可测性问题。

Detectability of Discrete Event Systems ( DES ) based on automata / languages is studied .

即使语言模型为描述JavaScript源代码和上下文提供了基础，还需要另外一个重要因素：环境上下文。

Even though the language model provides the basics for describing JavaScript source and context , another important piece is necessary : environment context .

最终通过实验验证了平滑优化N-gram统计语言模型以及挖掘纠错BadCase之后的良好纠错效果。

It is verified by experiment that eventually smoothed optimized N-gram statistical language models and error correction Bad Case mining have a nice effect for the search engine .

对CRF训练得到的语言模型采用N折交叉测试，商业实体全称的识别精确度达到了94.6%，召回率达到91.4%，平均F值达到92.9%。

Using N-folder cross to evaluate it , company full name recognition accuracy achieved 94.6 % , recall is 91.4 % , and F-Value is 92.9 % .

基于N-gram语言模型的汉字识别后处理研究

Post-processing Study of Chinese Character Recognition Based on N-gram Language Model

一种适应域的汉语N-gram语言模型平滑算法

Smoothing algorithm of the task adaptation Chinese N gram model

基于XML的工作流过程定义语言模型XMWPDL

XMWPDL : XML Based Workflow Definition Language

通过扩展Jelinek-Mercer平滑方法，该模型把passage特征成功地引入到了统计语言模型框架中。

By extending the Jelinek-Mercer smoothing , the new model successfully incorporates the passage feature into language model framework .

基于trigram语体特征分类的语言模型自适应方法

Language Model Adaptation Based on the Classification of a Trigram 's Language Style Feature

毕竟，Sphinx-4提供了大型词汇表字典和语言模型。

After all , Sphinx-4 provides large vocabulary dictionaries and language models .

实验表明，二者的结合在一定程度上克服了N元文法语言模型描述距离小于N的缺点，提高了系统的识别率。

Experiments show that the cooperation of these two models can overcome the shortcoming of N-gram model that it only can describe the word pairs being less than N words apart , and it also improves the word right rate of the system .

本文从文本检索模型的基本原理入手，分析了几种传统IR模型的优缺点，给出基于统计语言模型的IR模型的基本原理、关键技术以及它的优势所在。

This paper starts with the basic principle of text retrieval models , has analysed the pluses and minuses of several kinds of traditional IR models , given the basic principle , key technology and the advantage of statistical language model based IR models .

通过N元语言模型与传统分类模型（向量空间模型和NaiveBayes模型）的实验对比，结果表明：N元模型分类器具有更好的分类性能。

The performance of the N-gram model classifier was compared with that of the traditional models ( Vector Space Model and Naive Bayes Model ) . Experiment result shows that the accuracy and the stability of the N-gram model classifier are better than others .

根据最大限度纠正语言模型的转换错误和避免语言模型不平衡的原则，提出了适应汉语N-gram模型的机器学习方法。

A machine learning method suitable for Chinese N-gram model is proposed following the principle of correcting as much language model transfer errors as possible and avoiding language model imbalance .

通过在TREC测试集上进行的实验表明，相对于未进行查询扩展的简单的语言模型，本文的方法在检索性能上取得了一致性大幅的提高。

By the experiment on the TREC test set shows that , compared to a simple language model , this method has made consistent and substantial improvement . 3 .

最后，针对处理介词短语歧义时遇到的数据稀疏这一所有统计语言模型都面临的难题，分析介绍了基于N-Gram的回退法介词短语消歧及平滑技术。

Finally , in connection with the sparse data problem in the processing of PP disambiguation and current statistical language models , the author introduces the backed-off N-Gram based algorithm and similarity-based smoothing .

本文介绍了基于N-Gram的切分算法及语言模型，在其基础上，提出了一种改进的N-Gram切分算法，给出了一种结合N-Gram语言模型的贝叶斯过滤模型。

This thesis introduces segmentation algorithm and language model based on N-Gram . Then an improved N-Gram segmentation algorithm is proposed and an improved Bayesian filtering model based on N-Gram model is given .

数学模型导出了生物学零度（ki）和花期活动积温（∑Τi），图解模型对其进行了辨别，语言模型通过反馈回路对其进行验证实际效果。

The mathematical model was used to deduce biological zero point-joint ( Ki ) and bloom active temperature (Σ Ti ), which was studied by graphic model and language model , justifying the effect through feeding back loop .

实验结果表明这三个新模型的检索效果也显著超越了原有的简单语言模型，同时与PJM模型检索性能相当。

The results of experiments show that the new models have outperformed the simple language model significantly and that the performance of the new models is comparable to the PJM model .

然后本文比较了别的学者提出的方法与新的PJM模型，用实验证明了在统计语言模型框架下综合passage级别和文档级别两者信息相对仅仅使用passage级别信息也可以产生检索效果的提升。

Then this paper compares the PJM model with the method proposed by the other researchers . The experiments demonstrate that in the statistical language model framework compared with only using passage-level information combining the passage-level and document-level information can improve the model performance . 3 .

基于互信息的语言模型回退平滑算法

A back-off smoothing algorithm of language model based on mutual information

关于汉语音字转换中语言模型零概率的问题

Zero-Probabilities of Language Model in Translations of Chinese Spellings to Characters