3) n-gram model
n-gram模型
1.
This paper reviewed existing smoothing methods for N-gram model firstly,and implemented the Absolute,W-B and Katz smoothing algorithms respectively.
试验结果表明:新的Katz平滑算法降低了N-gram模型的交叉熵,在汉语分词中应用改进的平滑算法也提高了分词结果的F量度。
2.
We re-examine three classifiers: Bayes based on N-gram model classifier(NGBayes),Naive Bayes classifier(NBayes) and k-Nearest Neighbor classifier(kNN),which almost have the same performance in traditional text classification field.
本文是在噪音环境下文本分类方法的一种探索:把在传统文本分类中性能基本相当的基于N-gram模型的贝叶斯(NGBayes)、基于分词的朴素贝叶斯(NBayes)和基于分词的k近邻(kNN)分类方法应用到网页分类领域,在中文Web信息检索论坛提供的中文网页分类训练集——CCT2002-v1。
3.
This paper presents a new method for segmenting the input Chinese language text sentence into words, which consists of a character-based N-gram model and an efficient Viterbi search algorithm.
该文提出了一种将汉语文本句子切分成词的新方法,这种方法以N-gram模型为基础,并结合有效的Viterbi搜索算法来实现汉语句子的切词。
4) N-gram algorithm
N-gram算法
1.
This article presents a new method to identify new words by using tides and abstracts of jour- nal articles as training material,segmenting materials by N-gram algorithm and filtering words through stop word list.
本文提出了一种选择期刊论文的题名和摘要作为训练语料,利用N-gram算法切分和停用词典等过滤筛选的非专名的新词识别方法。
5) N-gram co-occurrence
N-gram共现
6) N-gram information
N-gram信息
补充资料：分布和特征量统计(见统计分析)
分布和特征量统计(见统计分析)
fenbu he tezhengliang tongjj分布和特征量统计见统计分析。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条