Collaborative Filtering: Weighted Nonnegative Matrix Factorization Incorporating User and Item Graphs
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[1] Fan Chung,et al. Spectral Graph Theory , 1996 .
[2] Y. Shoham,et al. Ecom Syst Content-based, Collaborative Recommendation , 1997 .
[3] John Riedl,et al. An algorithmic framework for performing collaborative filtering , 1999, SIGIR '99.
[4] Eric Horvitz,et al. Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach , 2000, UAI.
[5] H. Sebastian Seung,et al. Algorithms for Non-negative Matrix Factorization , 2000, NIPS.
[6] David M. Pennock,et al. Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments , 2001, UAI.
[7] John Riedl,et al. Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.
[8] Raymond J. Mooney,et al. Content-boosted collaborative filtering for improved recommendations , 2002, AAAI/IAAI.
[9] Bernhard Schölkopf,et al. Learning with Local and Global Consistency , 2003, NIPS.
[10] Alexander J. Smola,et al. Kernels and Regularization on Graphs , 2003, COLT.
[11] Tommi S. Jaakkola,et al. Weighted Low-Rank Approximations , 2003, ICML.
[12] Luo Si,et al. Flexible Mixture Model for Collaborative Filtering , 2003, ICML.
[13] Thomas Hofmann,et al. Unifying collaborative and content-based filtering , 2004, ICML.
[14] Thomas Hofmann,et al. Latent semantic models for collaborative filtering , 2004, TOIS.
[15] Luo Si,et al. An automatic weighting scheme for collaborative filtering , 2004, SIGIR '04.
[16] Tommi S. Jaakkola,et al. Maximum-Margin Matrix Factorization , 2004, NIPS.
[17] Gediminas Adomavicius,et al. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.
[18] Bernhard Schölkopf,et al. Learning from labeled and unlabeled data on a directed graph , 2005, ICML.
[19] Jun Wang,et al. Unifying user-based and item-based collaborative filtering approaches by similarity fusion , 2006, SIGIR.
[20] Mikhail Belkin,et al. Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples , 2006, J. Mach. Learn. Res..
[21] Fei Wang,et al. Recommendation on Item Graphs , 2006, Sixth International Conference on Data Mining (ICDM'06).
[22] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[23] Chris H. Q. Ding,et al. Orthogonal nonnegative matrix t-factorizations for clustering , 2006, KDD '06.
[24] Fillia Makedon,et al. Learning from Incomplete Ratings Using Non-negative Matrix Factorization , 2006, SDM.
[25] Punam Bedi,et al. Trust Based Recommender System for Semantic Web , 2007, IJCAI.
[26] Stephen Lin,et al. Graph Embedding and Extensions: A General Framework for Dimensionality Reduction , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Gang Chen,et al. Collaborative Filtering Using Orthogonal Nonnegative Matrix Tri-factorization , 2007, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007).
[28] Ruslan Salakhutdinov,et al. Probabilistic Matrix Factorization , 2007, NIPS.
[29] Jiawei Han,et al. Non-negative Matrix Factorization on Manifold , 2008, 2008 Eighth IEEE International Conference on Data Mining.
[30] Fei Wang,et al. Semi-Supervised Clustering via Matrix Factorization , 2008, SDM.
[31] Michael R. Lyu,et al. SoRec: social recommendation using probabilistic matrix factorization , 2008, CIKM '08.
[32] Quanquan Gu,et al. Transductive Classification via Dual Regularization , 2009, ECML/PKDD.
[33] Quanquan Gu,et al. Local Relevance Weighted Maximum Margin Criterion for Text Classification , 2009, SDM.
[34] Quanquan Gu,et al. Co-clustering on manifolds , 2009, KDD.
[35] Quanquan Gu,et al. Local Learning Regularized Nonnegative Matrix Factorization , 2009, IJCAI.
[36] Chris H. Q. Ding,et al. Convex and Semi-Nonnegative Matrix Factorizations , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.