计算机应用与软件2013，Vol.30Issue(5)：275-278,4.DOI:10.3969/j.issn.1000-386x.2013.05.078
基于背景知识和主动学习的文本挖掘技术研究
RESEARCH ON TEXT MINING BASED ON BACKGROUND KNOWLEDGE AND ACTIVE LEARNING
摘要
Abstract
In order to achieve good effect in text classification and text mining,there often needs to use a large number of labelled data.However,to label data is usually complex in operation and also expensive.Therefore,in this paper we introduce the unlabelled data to text classification and text mining in the framework of support vector machine-based classification technology.The specific implementation is carried out through two methods,the background knowledge-based and the active learning-based.Experimental results show that the text mining based on background knowledge can bring the text mining performance into excellent play under the condition of stronger baseline classifier,while the text mining based on active learning can improve the performance index of text mining just in general situation.关键词
文本挖掘/支持向量机/主动学习/背景知识Key words
Text mining/ Support vector machine / Active learning / Background knowledge分类
信息技术与安全科学引用本文复制引用
符保龙..基于背景知识和主动学习的文本挖掘技术研究[J].计算机应用与软件,2013,30(5):275-278,4.
