Computer Science ›› 2017, Vol. 44 ›› Issue (7): 309-314.doi: 10.11896/j.issn.1002-137X.2017.07.056

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Hypergraph Dual Regularization Concept Factorization Algorithm and Its Application in Data Representation

YE Jun and JIN Zhong   

  • Online:2018-11-13 Published:2018-11-13

Abstract: The concept factorization(CF) algorithm can not take the geometric structures of both the data manifold and the feature manifold into account simultaneously.And CF algorithm can not consider the high-order relationship among samples.In this paper,a novel algorithm called hypergraph dual regularization concept factorization(DHCF) algorithm was proposed,which encodes the high-order geometric structure information of data and feature spaces by constructing two undirected weighted hypergraph Laplacian regularize term,respectively.By this way,the proposed method can overcome the deficiency that traditional graph model expresses pair-wise relationship only.Moreover,we developed the iterative updating optimization schemes for DHCF,and provided the convergence proof of our optimization scheme.Experimental results on TDT2 document datasets,PIE and COIL20 image datasets demonstrate the effectiveness of our method.

Key words: CF,Hypergraph learning,Dual regularized,Manifold learning,Clustering

[1] YI Y G,SHI Y J,ZHANG H,et al.Label propagation based semi-supervised nonnegative matrix factorization for feature extraction[J].Neurocomputing,2015,149(PB):1021-1037.
[2] WANG M M,ZUO W L,WANG Y.A Multidimensional Personality Traits Recognition Model Based on Weighted Nonnegative Matrix Factorization[J].Chinese Journal of Computers,2016,39(38):1-17.(in Chinese) 王萌萌,左万利,王英.一种基于加权非负矩阵分解的多维用户人格特质识别算法[J].计算机学报,2016,39(38):1-17.
[3] HE C B,TANG Y,YANG A T,et al.Large-scale topic community mining based on distributed nonnegative matrix factorization[J].SCIENTIA SINICA Informationis,2016,46(6):714-728.(in Chinese) 贺超波,汤庸,杨阿祧,等.基于分布式非负矩阵分解的大规模主题社区挖掘[J].中国科学:信息科学,2016,46(6):714-728.
[4] LEE D D,SEUNG H S.Learning the parts of objects by non-negative matrix factorization[J].Nature,1999,401(6755):788-791.
[5] XU W,GONG Y H.Document clustering by concept factorization[C]∥International Conference on Research and Development in Information Retrieval.Sheffield,UK,2004:202-209.
[6] SHANG F H,JIAO L C,WANG F.Graph dual regularization non-negative matrix factorization for co-clustering[J].Pattern Recognition,2012,45(6):2237-2250.
[7] TENENBAUM J B,SILVA V D,LANGFORD J C.A global geo-metric framework for nonlinear dimensionality reduction[J].Science,2000,290(5500):2319-2323.
[8] ROWEIS S T,SAUL L K.Nonlinear dimensionality reduction by locally linear embedding[J].Science,2000,290(5500):2323-2326.
[9] BELKIN M,NIYOGI P.Laplacian Eigenmaps and spectral techniques for embedding and clustering[J].Advances in Neural Information Processing Systems,2001,14(6):585-591.
[10] HU X K,SUN F M,LI H J.Constrained Nonnegative MatrixFactorization with Sparseness for Image Representation[J].Computer Science,2015,42(7):280-284.(in Chinese) 胡学考,孙福明,李豪杰.基于稀疏约束的半监督非负矩阵分解算法[J].计算机科学,2015,42(7):280-284.
[11] FANG W T,MA P,CHENG Z B,et al.2-dimensional Projective Non-negative Matrix Factorization and Its Application to Face Recognition[J].Acta Automatica Sinica,2012,38(9):1503-1512.(in Chinese) 方蔚涛,马鹏,成正斌,等.二维投影非负矩阵分解算法及其在人脸识别中的应用[J].自动化学报,2012,38(9):1503-1512.
[12] CAI D,HE X F,HAN J W,et al.Graph regularization non-ne-gative matrix factorization for data representation[J].IEEE Trans.Pattern Analysis and Machine Intelligence,2011,33(8):1548-1560.
[13] WANG J Y,BENSMAIL H,GAO X.Multiple graph regularized nonnegative matrix factorization[J].Pattern Recognition,2013,46(10):2840-2847.
[14] GUAN N Y,TAO D C,LUO Z G,et al.Manifold regularized discriminative nonnegative matrix factorization with fast gra-dient descent[J].IEEE Trans on Image Processing,2011,20(7):2030-2048.
[15] CAI D,HE X F,HAN J W.Locally consistent concept factorization for document clustering[J].IEEE Transactions on Know-ledge and Data Engineering,2011,23(6):902-913.
[16] YE J,JIN Z.Dual-graph regularized concept factorization forclustering[J].Neurocomputing,2014,138(3):120-130.
[17] ZHOU D Y,HUANG J Y,SCHOLKOPF B.Learning with hypergraphs:clustering,classification and embedding[C]∥Advances in Neural Information Processing Systems,Vancouver,BC,Canada,2006:1601-1608.
[18] HUANG Y C,LIU Q S,ZHANG S T,et al.Image retrieval via probabilistic hypergraph ranking[C]∥Proceedings of the International Conference on Computer Vision and Pattern Recognition.San Francisco,USA,2010:3376-3383.
[19] WEI B,CHENG M,WANG C,et al.Combinative hypergraph learning for semi-supervised image classification [J].Neurocomputing,2015,153:217-277
[20] JIN T,YU J,YOU J,et al.Low-rank matrix factorization with multiple hypergraph regularizer [J].Pattern Recognition,2015,48(3):1011-1022.
[21] ZENG K,YU J,LI C,et al.Image clustering by hyper-graph re-gularized non-negative matrix factorization[J].Neurocompu-ting,2014,138(11):209-217.

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