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	Text representation: From vector to tensor
	Ning, Liu ; Benyu, Zhang ; Jun, Yan ; Zheng, Chen ; Wenyin, Liu ; Fengshan, Bai ; Leefeng, Chien
	2005
英文摘要	In this paper, we propose a text representation model, Tensor Space Model (TSM), which models the text by multilinear algebraic high-order tensor instead of the traditional vector. Supported by techniques of multilinear algebra, TSM offers a potent mathematical framework for analyzing the multifactor structures. TSM is further supported by certain introduced particular operations and presented tools, such as the High-Order Singular Value Decomposition (HOSVD) for dimension reduction and other applications. Experimental results on the 20 Newsgroups dataset show that TSM is constantly better than VSMfor text classification. ? 2005 IEEE.; EI; 0
语种	英语
出处	EI
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/328906]
专题	数学科学学院
推荐引用方式 GB/T 7714	Ning, Liu,Benyu, Zhang,Jun, Yan,et al. Text representation: From vector to tensor. 2005-01-01.

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