一种时空高效的多类别文本分类算法  

A space-time-efficient multi-category text categorization algorithm

作　　者：刘伍颖[1] 易绵竹[1] 张兴[1] 

机构地区：[1]解放军外国语学院,河南洛阳471003

出　　处：《山东大学学报（理学版）》2013年第11期99-104,共6页Journal of Shandong University(Natural Science)

摘　　要：低时空复杂度始终是多类别文本分类算法希望达到的性能。新闻文档集中Token频率分布的研究再次验证了Token频率分布普遍服从幂律。据此设计了一种新的多类别Token频率索引数据结构,并基于该数据结构提出了一种低时空复杂度的多类别文本分类算法。在TanCorp数据集上的实验结果表明该算法在多类别新闻文档分类应用中是时空高效的。Low space-time complexity is always the expected performance of multi-category text categorization algo- rithms. The investigation of token frequency distribution in the set of news documents validates that the token frequency distribution obeys the ubiquitous power law. According to the distribution property of power law, a novel data structure of multi-category token frequency index is designed and based on which a multi-category text categorization algorithm with low space-time complexity is propose. The experimental results on the TanCorp data set show that the proposed al- gorithm is space-time-efficient in the application of multi-category news document categorization.

关 键 词：多类别文本分类 算法复杂度 多类别Token频率索引 幂律 新闻文档 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]