基于松弛策略的文本层次分类方法  

Relaxed Hierarchy Structure Construction for Text Classification

作　　者：杜永萍[1] 杜晓燕[1] 陈守钦 

机构地区：[1]北京工业大学计算机学院

出　　处：《北京工业大学学报》2017年第8期1175-1181,共7页Journal of Beijing University of Technology

基　　金：国家科技支撑计划子课题资助项目(2013BAH21B02-01);北京市自然科学基金资助项目(4153058);上海市智能信息处理重点实验室开放基金资助项目(IIPL-2014-004)

摘　　要：为了进一步提高文本层次分类的性能,在传统层次分类方法的基础上融入了松弛策略思想,在构造层次结构的过程中,该方法推迟了不确定类别的节点判定,直到可以明确所属类别,大大降低了高层节点分类错误对低层节点分类性能的影响,即"阻滞"问题的有效缓解.实验结果表明:松弛策略思想可以构建更加合理的层次结构,并进一步提高了分类的性能;相对于支持向量机等其他分类方法,在时间性能上更加高效,对于大规模文本分类任务而言具有重要意义.Hierarchical classification is an effective method to solving the classification problem on the large-scale text data and it can save time without reducing the classification accuracy. A relaxed strategy combining the traditional hierarchical classification method to improving the system performance was introduced. During the process of hierarchy structure construction,the node juedgement of the uncertain category was delayed until it was classified clearly. T he “ block” problem was effectively alleviated to transfer the classification error from the higher level to the lower level in the hierarchy structure. The experimental results show that the relaxation approach can build a more reasonable hierarchy and further improve the classification performance. Compared to the other classification method, such as Support Vector Machines,the method has more advantage in time performance and is more efficient for large-scale text classification task.

关 键 词：松弛策略 层次分类 支持向量机 聚类 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]