文本分类中支持向量机研究  

Research on Support Vector Machine in Text Categorization

作　　者：何焱[1] HE Yan(Zunyi Medical and Pharmaceutical College,Zunyi Guizhou 563002)

机构地区：[1]遵义医药高等专科学校

出　　处：《河南科技》2019年第29期8-10,共3页Henan Science and Technology

基　　金：贵州省“千”层次创新型人才培养项目（遵市科合人才[2017]24号）

摘　　要：随着我国现代科技的快速发展,文本分类逐渐在信息化技术与数字化技术领域得到重视。利用计算处理系统处理文本信息,能够有效提升文本分类的质量与效率,提升数据信息的利用率,从而促进信息化技术的普及。而支持向量机是处理文本内容,加强文本分类速度,并通过文档建模、中文分词、分类器评估等形式,构建出的行之有效的统计语言模型,它可以推动文本分类工作的发展。本文结合国内外研究现状,探析文本分类内涵及支持向量机原理,提出基于支持向量机的文本分类算法。With the rapid development of modern science and technology in China, text classification has gradually gained attention in the field of information technology and digital technology. The use of the computing processing system to process text information can effectively improve the quality and efficiency of text classification, improve the utilization of data information, and promote the popularization of information technology. The support vector machine is a statistical language model that is effective in processing text content, enhancing text classification speed, and constructing it through document modeling, Chinese word segmentation, and classifier evaluation, which can promote the development of text classification work. Based on the research status at home and abroad, this paper analyzed the text classification connotation and the principle of support vector machine, and proposed a text classification algorithm based on support vector machine.

关 键 词：文本分类 支持向量机 统计语言模型 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]