中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
An improved centroid classifier for text categorization

文献类型:期刊论文

作者Tan, Songbo
刊名EXPERT SYSTEMS WITH APPLICATIONS
出版日期2008-07-01
卷号35期号:1-2页码:279-285
关键词text classification information retrievals data mining
ISSN号0957-4174
DOI10.1016/j.eswa.2007.06.028
英文摘要In the context of text categorization, Centroid Classifier has proved to be a simple and yet efficient method. However, it often suffers from the inductive bias or model misfit incurred by its assumption. In order to address this issue, we propose a novel batch-updated approach to enhance the performance of Centroid Classifier. The main idea behind this method is to take advantage of training errors to successively update the classification model by batch. The technique is simple to implement and flexible to text data. The experimental results indicate that the technique can significantly improve the performance of Centroid Classifier. (c) 2007 Elsevier Ltd. All rights reserved.
WOS研究方向Computer Science ; Engineering ; Operations Research & Management Science
语种英语
WOS记录号WOS:000257617100028
出版者PERGAMON-ELSEVIER SCIENCE LTD
源URL[http://119.78.100.204/handle/2XEOYT63/11385]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Tan, Songbo
作者单位Chinese Acad Sci, Inst Comp Technol, Intelligent Software Dept, Beijing, Peoples R China
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GB/T 7714
Tan, Songbo. An improved centroid classifier for text categorization[J]. EXPERT SYSTEMS WITH APPLICATIONS,2008,35(1-2):279-285.
APA Tan, Songbo.(2008).An improved centroid classifier for text categorization.EXPERT SYSTEMS WITH APPLICATIONS,35(1-2),279-285.
MLA Tan, Songbo."An improved centroid classifier for text categorization".EXPERT SYSTEMS WITH APPLICATIONS 35.1-2(2008):279-285.

入库方式: OAI收割

来源:计算技术研究所

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