Binary k-nearest neighbor for text categorization

doi:10.1108/14684520510617839

	Binary k-nearest neighbor for text categorization
	Tan, SB
	2005
发表期刊	ONLINE INFORMATION REVIEW
ISSN	1468-4527
卷号	29 期号:4 页码:391-399
摘要	Purpose - With the ever-increasing volume of text data via the internet, it is important that documents are classified as manageable and easy to understand categories. This paper proposes the use of binary k-nearest neighbour (BKNN) for text categorization. Design/methodology/approach - The paper describes the traditional k-nearest neighbor (KNN) classifier, introduces BKNN and outlines experiemental results. Findings - The experimental results indicate that BKNN requires much less CPU time than KNN, without loss of classification performance. Originality/value - The paper demonstrates how BKNN can be an efficient and effective algorithm for text categorization. Proposes the use of binary k-nearest neighbor (BKNN) for text categorization.
关键词	classification information retrieval data handling
DOI	10.1108/14684520510617839
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Information Science & Library Science
WOS类目	Computer Science, Information Systems ; Information Science & Library Science
WOS记录号	WOS:000232354500005
出版者	EMERALD GROUP PUBLISHING LIMITED
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/10292
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, SB
作者单位	Chinese Acad Sci, Software Dept, Comp Technol Inst, Beijing 100864, Peoples R China
推荐引用方式 GB/T 7714	Tan, SB. Binary k-nearest neighbor for text categorization[J]. ONLINE INFORMATION REVIEW,2005,29(4):391-399.
APA	Tan, SB.(2005).Binary k-nearest neighbor for text categorization.ONLINE INFORMATION REVIEW,29(4),391-399.
MLA	Tan, SB."Binary k-nearest neighbor for text categorization".ONLINE INFORMATION REVIEW 29.4(2005):391-399.