Similarity measure based on improved optimal assignment model

doi:10.1109/IHMSC.2010.39

CORC > 兰州理工大学 > 兰州理工大学

	Similarity measure based on improved optimal assignment model
	Zhang, Yong; Deng, Ke
	2010
关键词	Document Clustering Hungarian algorithm Machine translations Measuring similarities Optimal assignment Semantic similarity Similarity measure Traditional models
卷号	1
DOI	10.1109/IHMSC.2010.39
页码	125-128
英文摘要	Measuring similarity has a wide range of application in information retrieval, machine translation or other related fields. In this paper, we proposed a text similarity computation based on improved optimal assignment model, which combine the improved Hungarian algorithm with the semantic similarity of terms to obtain the maximum semantic similarity between two documents or between a query and a document. Experiment shows that the algorithm has a significant improvement for semantic similarity comparing to traditional models of similarity measure. the method can be applied to document clustering, which will enchance the accuracy of result. © 2010 IEEE.
会议录	Proceedings - 2010 2nd International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2010
会议录出版者	IEEE Computer Society
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/116067]
专题	兰州理工大学
作者单位	College of Computer and Communication, LanZhou University of Technology, Lanzhou, China
推荐引用方式 GB/T 7714	Zhang, Yong,Deng, Ke. Similarity measure based on improved optimal assignment model[C]. 见:.