文本分类C#实现

A Text Categorization System with C#

设计并实现一个基于向量空间模型和简单贝叶斯的文本分类系统,系统采用层级多标签的分类策略。详细介绍词语切分统计、终分类器值计算、层级小类校正和兼类判断四个子系统模块。基于向量空间模型分类的第一级大类和层级小类的微平均分别为89.7%和77.8%,简单贝叶斯分别为67.6%和66.5%。

Based on Vector Space Model（VSM） and Naive - Bayes（ NB）, completed a multilayer and multi - classification text categorization system. Introduce detailedly four modules： words＇ segmentation and frequency statistics, calculating between classifications＇ and document, emendating the veracity of parent - class by emendation of subclass, judging whether document has multi - classification and multi - label. Text representation based on Vector Space Model has 89.7% MicroFl of parent - category, 77.8% of sub - category ; text representation based on Naive - Bayes has 67.6% MicroFl of parent - category, 66.5% of sub - category.