Article

NMF and PLSI: equivalence and a hybrid algorithm

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SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 641 - 642

https://doi.org/10.1145/1148170.1148295

Published: 06 August 2006 Publication History

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Abstract

In this paper, we show that PLSI and NMF optimize the same objective function, although PLSI and NMF are different algorithms as verified by experiments. In addition, we also propose a new hybrid method that runs PLSI and NMF alternatively to achieve better solutions.

References

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C. Ding, X. He, and H.D. Simon. On the equivalence of nonnegative matrix factorization and spectral clustering. Proc. SIAM Data Mining Conf, 2005.

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C. Ding, T. Li, and W. Peng. Nonnegative matrix factorization and probabilistic latent semantic indexing: Equivalence, chi-square statistic, and a hybrid method. In AAAI, 2006.

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E. Gaussier and C. Goutte. Relation between PLSI and NMF and implications. In SIGIR, 2005.

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T. Hofmann. Probabilistic latent semantic analysis. In UAI), 1999.

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D.D. Lee and H. S. Seung. Algorithms for non-negative matrix factorization. In T. G. Dietterich and V. Tresp, editors, NIPS 13, 2001.

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T. Li, S. Ma, and M. Ogihara. Document clustering via adaptive subspace iteration. In SIGIR, 2004.

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Cited By

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Wang ZMa LZhang Y(2017)A Hybrid Machine Learning Method for Finding Depression Related Publications by Eliminating Outlier Publications2017 IEEE International Conference on Information Reuse and Integration (IRI)10.1109/IRI.2017.75(171-176)Online publication date: Aug-2017
https://doi.org/10.1109/IRI.2017.75
Bassiou NKotropoulos C(2014)Online PLSA: Batch Updating Techniques Including Out-of-Vocabulary WordsIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2014.229980625:11(1953-1966)Online publication date: Nov-2014
https://doi.org/10.1109/TNNLS.2014.2299806
Wahabzada MKersting K(2011)Larger residuals, less workProceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III10.5555/2034161.2034193(475-490)Online publication date: 5-Sep-2011
https://dl.acm.org/doi/10.5555/2034161.2034193
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Index Terms

NMF and PLSI: equivalence and a hybrid algorithm
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
        Cluster analysis

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Published In

SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval

August 2006

768 pages

ISBN:1595933697

DOI:10.1145/1148170

General Chair:
Efthimis N. Efthimiadis
University of Washington
,
Program Chairs:
Susan Dumais
Microsoft Research, Redmond
,
David Hawking
CSIRO ICT Centre, Canberra, Australia
,
Kalervo Järvelin,
University of Tampere, Finland

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 August 2006

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SIGIR06

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SIGIR06: The 29th Annual International SIGIR Conference

August 6 - 11, 2006

Washington, Seattle, USA

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

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Wang ZMa LZhang Y(2017)A Hybrid Machine Learning Method for Finding Depression Related Publications by Eliminating Outlier Publications2017 IEEE International Conference on Information Reuse and Integration (IRI)10.1109/IRI.2017.75(171-176)Online publication date: Aug-2017
https://doi.org/10.1109/IRI.2017.75
Bassiou NKotropoulos C(2014)Online PLSA: Batch Updating Techniques Including Out-of-Vocabulary WordsIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2014.229980625:11(1953-1966)Online publication date: Nov-2014
https://doi.org/10.1109/TNNLS.2014.2299806
Wahabzada MKersting K(2011)Larger residuals, less workProceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III10.5555/2034161.2034193(475-490)Online publication date: 5-Sep-2011
https://dl.acm.org/doi/10.5555/2034161.2034193
Wahabzada MKersting KPilz ABauckhage C(2011)More influence means less workProceedings of the 20th ACM international conference on Information and knowledge management10.1145/2063576.2063944(2273-2276)Online publication date: 24-Oct-2011
https://dl.acm.org/doi/10.1145/2063576.2063944
Wahlgreen BHansen L(2011)Large scale topic modeling made practical2011 IEEE International Workshop on Machine Learning for Signal Processing10.1109/MLSP.2011.6064628(1-6)Online publication date: Sep-2011
https://doi.org/10.1109/MLSP.2011.6064628
Wahabzada MKersting K(2011)Larger residuals, less workProceedings of the 2011th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part III10.1007/978-3-642-23808-6_31(475-490)Online publication date: 5-Sep-2011
https://dl.acm.org/doi/10.1007/978-3-642-23808-6_31
Wang DLi TDing C(2010)Weighted Feature Subset Non-negative Matrix Factorization and Its Applications to Document UnderstandingProceedings of the 2010 IEEE International Conference on Data Mining10.1109/ICDM.2010.47(541-550)Online publication date: 13-Dec-2010
https://dl.acm.org/doi/10.1109/ICDM.2010.47
Cao BSun JXiang EHu DYang QChen ZCheung DSong IChu WHu XLin J(2009)PQCProceedings of the 18th ACM conference on Information and knowledge management10.1145/1645953.1646108(1217-1226)Online publication date: 2-Nov-2009
https://dl.acm.org/doi/10.1145/1645953.1646108
Tang JLewis PLuo JGuan LHanjalic AKankanhalli MLee I(2008)Non-negative matrix factorisation for object class discovery and image auto-annotationProceedings of the 2008 international conference on Content-based image and video retrieval10.1145/1386352.1386370(105-112)Online publication date: 7-Jul-2008
https://dl.acm.org/doi/10.1145/1386352.1386370

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