Group matrix factorization for scalable topic modeling

SIGIR'12 - Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2012, Pages 375-384

  Wang, Quan ^a   Cao, Zheng ^b   Xu, Jun ^c   Li, Hang ^c  

^a PEKING UNIVERSITY   (China)

^b SHANGHAI JIAO TONG UNIVERSITY   (China)

^c MICROSOFT RESEARCH ASIA   (China)

Author keywords

large scale; matrix factorization; topic modeling

Indexed keywords

DATA SETS; DOCUMENT CLASSIFICATION; GROUP MATRICES; LARGE DATASETS; LARGE SCALE; LATENT STRUCTURES; MATRIX FACTORIZATIONS; MODELING APPROACH; NON-PROBABILISTIC; OBJECTIVE FUNCTIONS; REAL-WORLD APPLICATION; RELEVANCE RANKING; SCALING-UP; SEMANTIC CLASS; TEXT DOCUMENT; WIKIPEDIA;

EFFICIENCY; EXPERIMENTS; INFORMATION RETRIEVAL; SCALABILITY; SEMANTICS;

INFORMATION RETRIEVAL SYSTEMS;

EID: 84866634599     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2348283.2348335     Document Type: Conference Paper

References (28)

1. S. Bengio, F. Pereira, and Y. Singer. Group sparse coding. In NIPS, pages 82-89, 2009.
2. P. N. Bennett, K. M. Svore, and S. T. Dumais. Classification-enhanced ranking. In WWW, pages 111-120, 2010.
3. D. Blei. Introduction to probabilistic topic models. COMMUN ACM, to appear, 2011.
4. D. Blei and J. McAuliffe. Supervised topic models. In NIPS, pages 121-128, 2008.
5. D. Blei, A. Y. Ng, and M. I. Jordan. Latent dirichlet allocation. JMLR, 3:993-1022, 2003.
6. S. S. Chen, D. L. Donoho, and M. A. Saunders. Atomic decomposition by basis pursuit. SISC, 20:33-61, 1998.
7. S. Deerwester, S. T. Dumais, G. W. Furnas, T. K. Landauer, and R. Harshman. Indexing by latent semantic analysis. J AM SOC INFORM SCI, 41:391-407, 1990.
8. B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani. Least angle regression. ANN STAT, 32:407-499, 2004.
9. J. Friedman, T. Hastie, H. Hofling, and R. Tibshirani. Pathwise coordinate optimization. ANN APPL STAT, 1:302-332, 2007.
10. W. J. Fu. Penalized regressions: The bridge versus the lasso. J COMPUT GRAPH STAT, 7:397-416, 1998.
11. T. Hofmann. Probabilistic latent semantic indexing. In SIGIR, pages 50-57, 1999.
12. S. Lacoste-Julien, F. Sha, and M. I. Jordan. Disclda: Discriminative learning for dimensionality reduction and classification. In NIPS, pages 897-904, 2008.
13. D. D. Lee and H. S. Seung. Learning the parts of objects with nonnegative matrix factorization. Nature, 401:391-407, 1999.
14. D. D. Lee and H. S. Seung. Algorithms for non-negative matrix factorization. In NIPS 13, pages 556-562. 2001.
15. H. Lee, A. Battle, R. Raina, and A. Y. Ng. Efficient sparse coding algorithms. In NIPS, pages 801-808. 2007.
16. H. Lee and S. Choi. Group nonnegative matrix factorization for eeg classification. In AISTATS, pages 320-327, 2009.
17. J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman. Discriminative learned dictionaries for local image analysis. In CVPR, 2008.
18. J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman. Supervised dictionary learning. In NIPS, pages 1033-1040. 2009.
19. D. M. Mimno and McCallum. Organizing the oca: Learning faceted subjects from a library of digital books. In JCDL, pages 376-385, 2007.
20. B. A. Olshausen and D. J. Fieldt. Sparse coding with an overcomplete basis set: a strategy employed by v1. VISION RES, 37:3311-3325, 1997.
21. M. Osborne, B. Presnell, and B. Turlach. A new approach to variable selection in least squares problems. IMA J NUMER ANAL, 2000.
22. D. Ramage, C. D. Manning, and S. Dumais. Partially labeled topic models for interpretable text mining. In SIGKDD, pages 457-465, 2011.
23. S. E. Robertson, S. Walker, S. Jones, M. Hancock-Beaulieu, and M. Gatford. Okapi at trec-3. In TREC'3, 1994.
24. G. Salton, A. Wong, and C. S. Yang. A vector space model for automatic indexing. Commun. ACM, 18:613-620, 1975.
25. F. Wang, N. Lee, J. Sun, J. Hu, and S. Ebadollahi. Automatic group sparse coding. In AAAI, pages 495-500, 2011.
26. Q. Wang, J. Xu, H. Li, and N. Craswell. Regularized latent semantic indexing. In SIGIR, pages 685-694, 2011.
27. X. Wei and B. W. Croft. Lda-based document models for ad-hoc retrieval. In SIGIR, pages 178-185, 2006.
28. C. Zhai, A. Velivelli, and B. Yu. A crosscollection mixture model for comparative text mining. In SIGKDD, pages 743-748, 2004.