text segment

Many researches indicate that text classification is a feasible way. A Naive Bayesian Algorithm is proposed in this paper to model the filtering and a N-gram method is also introduced to segment the Chinese text into word.

本文使用了基于简单贝叶斯模型的过滤算法，同时使用N-gram对中文文本进行自动分词，并且组合多个N-gram来加快分类的收敛速度，这样分类是一种切实可行的垃圾邮件过滤方法。

Experimental results show that the proposed method possesses better performance than that based on the CRFs simply segment text into total words or blocks.

实验结果表明，该方法的抽取性能，优于基于词或者块的条件随机场模型的信息抽取方法。

First, the model used Local Ambiguity Word Grid algorithm to generate rough segmentation results in the lower level. Then, segment the text again based on CRFs, and set the rough results as one feature.

首先，在低层使用局部歧义词网格对文本粗切分，并将切分结果作为一项特征提供给高层的CRFs模型；然后，在高层使用条件随机场对文本进行字标注。

According to the structure and storage of the directory, we design and apply a word segmentation algorithm on the text to segment the words and label the features.

然后使用一种适合目录信息的结构和存储格式的分词方法，对目录文本进行分词处理并对目录信息中的特征项进行标注。

Research of Separating Eleven Segment in Text Processing

划分11段的思想在文本处理方面的研究

Studies on Text Segment Algorithms' Influence on Chinese-based Information Filtering

文本分割算法对中文信息过滤影响研究

Considering the special structure of question database, a vector space search model based on text segment is adopted. An improvement on the traditional TF-IDF formula is made, and local similarity and global similarity are combined to sort the search results.

针对题库结构的特殊性，采用了基于文本段的向量空间搜索模型，对传统的TF-IDF公式做了改进，并使用局部相似度和全局相似度相结合的方法实现搜索结果的排序。