基于张量模型的多因素影响程度分析方法

doi:10.3778/j.issn.1002-8331.1608-0323

CORC > 北京大学 > 信息科学技术学院

	基于张量模型的多因素影响程度分析方法; Multi factors influencing degree analysis method based on tensor model
	王卿云 ; 李红燕 ; 洪申达
刊名	计算机工程与应用
	2017
关键词	影响因素影响程度分析预处理张量分解与重建 influencing factors influencing degree analysis preprocessing tensor decomposition and reconstruction
DOI	10.3778/j.issn.1002-8331.1608-0323
英文摘要	影响程度分析分为独立影响程度分析和联合影响程度分析.传统的影响程度分析方法难以兼顾二者,并且在分析的过程中受困于影响因素数目过多以及因素之间复共线性的干扰.部分方法甚至难以应对大规模数据集,这些问题无疑阻碍了方法分析准确率的提升以及广泛应用.于是基于此提出了基于张量分解与重建的多因素影响程度分析方法(MAT),消除了影响因素之间的复共线性,全面而准确地分析了单一因素的独立影响程度和多因素的联合影响程度.通过在真实大规模移动通信数据集上的实验,验证了MAT方法的有效性和准确性.; The influencing degree analysis can be divided into independent influencing degree analysis and the combined influencing degree analysis. The traditional influencing degree analysis method is difficult to take the two into account, and is trapped in the number of influencing factors and multicollinearity between factors. Some methods even cannot be applied to large scale data sets, which undoubtedly hinder the improvement of the accuracy of the analysis and the wide application of the methods. So it proposes the Multi factors influencing degree Analysis method based on Tensor decom-position and reconstruction(MAT), which eliminates the multicollinearity between factors, and realizes the analysis of independent and combined influencing degree at the same time. The experiments on the real large scale mobile communi-cation data set have showed the validity and accuracy of the MAT.; 国家自然科学基金; 17; 94-100,165; 53
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/465257]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	王卿云,李红燕,洪申达. 基于张量模型的多因素影响程度分析方法, Multi factors influencing degree analysis method based on tensor model[J]. 计算机工程与应用,2017.
APA	王卿云,李红燕,&洪申达.(2017).基于张量模型的多因素影响程度分析方法.计算机工程与应用.
MLA	王卿云,et al."基于张量模型的多因素影响程度分析方法".计算机工程与应用 (2017).