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Volumn , Issue , 2010, Pages

Deterministic single-pass algorithm for LDA

Author keywords

[No Author keywords available]

Indexed keywords

BATCH ALGORITHMS; DETERMINISTICS; LATENT DIRICHLET ALLOCATION; SINGLE-PASS ALGORITHM; TEXT STREAMS;

EID: 85161976784     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (17)

References (15)
  • 1
    • 67049100147 scopus 로고    scopus 로고
    • On-line lda: Adaptive topic models for mining text streams with applications to topic detection and tracking
    • ISSN 1550-4786
    • Loulwah Alsumait, Daniel Barbara, and Carlotta Domeniconi. On-line lda: Adaptive topic models for mining text streams with applications to topic detection and tracking. IEEE International Conference on Data Mining, 0:3-12, 2008. ISSN 1550-4786.
    • (2008) IEEE International Conference on Data Mining , pp. 3-12
    • Alsumait, L.1    Barbara, D.2    Domeniconi, C.3
  • 3
    • 70449126967 scopus 로고    scopus 로고
    • Topic models over text streams: A study of batch and online unsupervised learning
    • Arindam Banerjee and Sugato Basu. Topic models over text streams: A study of batch and online unsupervised learning. In SIAM International Conference on Data Mining, 2007.
    • (2007) SIAM International Conference on Data Mining
    • Banerjee, A.1    Basu, S.2
  • 9
    • 0141596527 scopus 로고    scopus 로고
    • Estimating a dirichlet distribution
    • Thomas P. Minka. Estimating a dirichlet distribution. Technical report, Microsoft, 2000. URL http://research.microsoft.com/-minka/papers/dirichlet/ minka-dirichlet.pdf.
    • (2000) Technical Report, Microsoft
    • Minka, T.P.1
  • 10
    • 0003931083 scopus 로고    scopus 로고
    • Using lower bounds to approximate integrals
    • Thomas P. Minka. Using lower bounds to approximate integrals. Technical report, Microsoft, 2001. URL http://research.microsoft.com/en-us/um/people/ minka/papers/rem.html.
    • (2001) Technical Report, Microsoft
    • Minka, T.P.1
  • 11
    • 0002788893 scopus 로고    scopus 로고
    • A view of the em algorithm that justifies incremental, sparse, and other variants
    • M. I. Jordan, editor, Kluwer
    • R. Neal and G. Hinton. A view of the EM algorithm that justifies incremental, sparse, and other variants. In M. I. Jordan, editor, Learning in Graphical Models. Kluwer, 1998. URL http://citeseerx.ist.psu.edu/viewdoc/ summary?doi=10.1.1.33.2557.
    • (1998) Learning in Graphical Models
    • Neal, R.1    Hinton, G.2
  • 12
    • 0034131785 scopus 로고    scopus 로고
    • On-line em algorithm for the normalized gaussian network
    • Masa A. Sato and Shin Ishii. On-line em algorithm for the normalized gaussian network. Neural Computation, 12(2):407-432, 2000. URL http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.3704.
    • (2000) Neural Computation , vol.12 , Issue.2 , pp. 407-432
    • Sato, M.A.1    Ishii, S.2
  • 14
    • 79952129745 scopus 로고    scopus 로고
    • Rethinking lda: Why priors matter
    • Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors
    • Hanna Wallach, David Mimno, and Andrew McCallum. Rethinking lda: Why priors matter. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors, Advances in Neural Information Processing Systems 22, pages 1973-1981. 2009.
    • (2009) Advances in Neural Information Processing Systems , vol.22 , pp. 1973-1981
    • Wallach, H.1    Mimno, D.2    McCallum, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.