摘要
文本分类是自然语言处理领域的一个重要分支,它不仅能对文本信息进行高效的分类和管理,而且能为自然语言处理其它方面的应用提供良好的理论支撑和技术支撑。近年来文本分类的研究在很多领域都取得了显著的成果,但由于文本分类在国内起步较晚,涉及领域较多,目前还有较多的工作需要进一步的研究和完善。基于此,从技术、方法和应用几个方面介绍了空间向量模型的文本分类的研究近况,以期为该领域的相关研究提供借鉴。
Text categorization is an important branch of natural language processing.It not only can efficiently classify and manage text information,but also provide good theoretical and technical support for other aspects of natural language processing.In recent years,the research on text categorization has achieved good achievements in many fields.However,since text categorization started late in China and involves many fields,there are still much work that needs further research and improvement.Based on this,this paper introduces the research status of text categorization of space vector model from the aspects of technology,method and application,analyzes some problems existing in textcategorization,and gives several possible application trends.
作者
吴龙峰
于瓅
王峰
WU Longfeng;YU Li;WANG Feng(College of Computer Science and Engineering,Anhui University of Science&Technology,Huainan 232001,China;School of Computer and Information Engineering,Fuyang Normal University,Fuyang 236037,China)
出处
《宿州学院学报》
2019年第12期69-72,76,共5页
Journal of Suzhou University
关键词
自然语言处理
文本分类
向量空间模型
特征选取
文本表示
Natural language processing
Text categorization
Space vector model
Feature extraction
Text representation