| 文本分类C#实现* |
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| 引用本文： | 刘华. 文本分类C#实现*[J]. 现代图书情报技术, 2007, 2(3): 43-45 |
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| 作者姓名： | 刘华 |
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| 作者单位： | 暨南大学华文学院/海外华语研究中心,广州,510610 |
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| 基金项目： | 教育部国家语言资源监测项目 |
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| 摘 要： | 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%。
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| 关 键 词： | 向量空间模型 简单贝叶斯 |
| 收稿时间： | 2007-01-29 |
| 修稿时间： | 2007-01-27 |
A Text Categorization System with C# |
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| Liu Hua. A Text Categorization System with C#[J]. New Technology of Library and Information Service, 2007, 2(3): 43-45 |
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| Authors: | Liu Hua |
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| Affiliation: | College of Chinese Language and Culture/Center for Overseas Huayu Research, Jinan University, Guangzhou 510610, China |
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| Abstract: | Based on Vector Space Model(VSM) and Nave-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% MicroF1 of parent- category, 77.8% of sub- category; text representation based on Nave-Bayes has 67.6% MicroF1 of parent- category, 66.5% of sub- category. |
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| Keywords: | Text categorization Vector space model Na-Bayes |
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