[1]徐猛,王靖,杜吉祥.采用邻域关联性的非监督流形对齐算法[J].华侨大学学报(自然科学版),2018,39(2):256-261.[doi:10.11830/ISSN.1000-5013.201601015]
　XU Meng,WANG Jing,DU Jixiang.Unsupervised Manifold Alignment Algorithm Using Neighborhood Correlation[J].Journal of Huaqiao University(Natural Science),2018,39(2):256-261.[doi:10.11830/ISSN.1000-5013.201601015]
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采用邻域关联性的非监督流形对齐算法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第39卷
期数:
2018年第2期
页码:
256-261
栏目:
出版日期:
2018-03-20

文章信息/Info

Title:
Unsupervised Manifold Alignment Algorithm Using Neighborhood Correlation
文章编号:
1000-5013(2018)02-0256-06
作者:
徐猛;  王靖;  杜吉祥
华侨大学 计算机科学与技术学院, 福建 厦门 361021
Author(s):
XU Meng;  WANG Jing;  DU Jixiang
College of Computer Science and Technology, Huaqiao University, Xiamen 361021, China
关键词:
流形对齐;  关联性;  局部邻域;  非监督
Keywords:
manifold alignment;  correlation;  local neighborhood;  unsupervised
分类号:
TP301.6
DOI:
10.11830/ISSN.1000-5013.201601015
文献标志码:
A
摘要:
假设对于两个流形上关联性较强的样本点,其邻域点之间也会具有较强的关联性.基于此假设,提出一种新的非监督流形对齐算法,通过学习局部邻域之间的关联性,挖掘不同流形样本点间的关联性;然后,将两个流形样本点投影到共同的低维空间,同时保持所挖掘的关联性.结果表明:与传统的非监督流形对齐算法比较,文中算法能更准确地找出不同流形数据在低维空间的匹配点.
Abstract:
This paper propose a basic assumption: for the points sampled from two manifolds which have strong correlations, their neighbors also have stronger correlations. Based on this assumption, this paper propose a new unsupervised manifold alignment algorithm which using the local neighborhood correlation to construct the relationship between the data sample points from different manifolds, and then projecting two manifold data to a common low-dimensional space while preserve the discovering of the correlation. The numerical experiments show that compared with the traditional unsupervised manifold alignment algorithms, this proposed algorithm can find the matching points of different manifold data in the low-dimensional space more accurately.

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备注/Memo

备注/Memo:
收稿日期: 2016-01-10
通信作者: 王靖(1981-),男,教授,博士,主要从事模式识别、推荐系统的研究.E-mail:wroaring@hqu.edu.cn.
基金项目: 国家自然科学基金资助项目(61370006); 福建省自然科学基金资助项目(2014J01237); 福建省教育厅科技项目(JA12006); 福建省高等学校新世纪优秀人才支持计划(2012FJ-NCET-ZR01); 华侨大学中青年教师科技创新资助计划(ZQN-PY116)
更新日期/Last Update: 2018-03-20