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Volumn 10, Issue 3, 2005, Pages 175-196

Sequential activity profiling: Latent dirichlet allocation of Markov chains

Author keywords

Markov chains; Mixture models; User profiling

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; MATHEMATICAL MODELS; MATHEMATICAL OPERATORS; WEB BROWSERS; WORLD WIDE WEB;

EID: 22044450174     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-005-0362-2     Document Type: Article
Times cited : (25)

References (26)
  • 2
    • 22044457666 scopus 로고    scopus 로고
    • Learning in high dimension: Modular mixture models
    • Attias, H. 2001. Learning in high dimension: modular mixture models. In Proc. AI and Statistics.
    • (2001) Proc. AI and Statistics.
    • Attias, H.1
  • 8
    • 0034818212 scopus 로고    scopus 로고
    • Unsupervised learning by probabilistic latent semantic analysis
    • Hofmann, T. 2001. Unsupervised learning by probabilistic latent semantic analysis. Machine Learning, 42:177-196.
    • (2001) Machine Learning , vol.42 , pp. 177-196
    • Hofmann, T.1
  • 10
    • 84950443107 scopus 로고
    • Maximum likelihood estimation in the mover-stayer model
    • Frydman, H. 1984. Maximum likelihood estimation in the mover-stayer model. Journal of the American Statistical Society, 79:632-638.
    • (1984) Journal of the American Statistical Society , vol.79 , pp. 632-638
    • Frydman, H.1
  • 11
    • 0028181441 scopus 로고    scopus 로고
    • Hidden Markov Models in computational biology: Applications to protein modelling
    • Krogh, A. Hidden Markov Models in computational biology: Applications to protein modelling. Journal of Molecular Biology, 235:1501-1531.
    • Journal of Molecular Biology , vol.235 , pp. 1501-1531
    • Krogh, A.1
  • 12
    • 84898964201 scopus 로고    scopus 로고
    • Algorithms for Non-negative Matrix Factorization
    • Todd K. Leen, Thomas G. Dietterich, and Volker. Tresp, (eds.) MIT Press
    • Lee, D. and Sebastian Seung, H. 2001. Algorithms for Non-negative Matrix Factorization. In Advances in Neural Information Processing Systems 13, Todd K. Leen, Thomas G. Dietterich, and Volker. Tresp, (eds.) MIT Press, pp. 556-562.
    • (2001) Advances in Neural Information Processing Systems , vol.13 , pp. 556-562
    • Lee, D.1    Sebastian Seung, H.2
  • 18
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected applications in speech recognition
    • Rabiner, L.R. 1989. A tutorial on hidden Markov models and selected applications in speech recognition. In Proc. of the IEEE, 77(2):257-285.
    • (1989) Proc. of the IEEE , vol.77 , Issue.2 , pp. 257-285
    • Rabiner, L.R.1
  • 20
    • 0141484919 scopus 로고
    • Maximum likelihood estimation of Dirichlet distributions
    • Ronning, G. 1989. Maximum likelihood estimation of Dirichlet distributions. Journal of Statistical Computation and Simulation, 32(4):215-221.
    • (1989) Journal of Statistical Computation and Simulation , vol.32 , Issue.4 , pp. 215-221
    • Ronning, G.1
  • 21
    • 22044444083 scopus 로고    scopus 로고
    • Multiple-cause vector quantiztion
    • S. Becker, S. Thrun and K. Obermayer (Eds.), MIT Press
    • Ross, D.A. and Zemel, R.S. 2003. Multiple-cause vector quantiztion. In Advances in Neural Information Processing Systems 15, S. Becker, S. Thrun and K. Obermayer (Eds.), MIT Press, pp. 1017-1024.
    • (2003) Advances in Neural Information Processing Systems , vol.15 , pp. 1017-1024
    • Ross, D.A.1    Zemel, R.S.2
  • 22
    • 0033723107 scopus 로고    scopus 로고
    • Link prediction and path analysis using markov chains
    • Sarukkai, R. 2000. Link prediction and path analysis using markov chains. Computer Networks, 33(1-6):377-386.
    • (2000) Computer Networks , vol.33 , Issue.1-6 , pp. 377-386
    • Sarukkai, R.1
  • 24
    • 0032596518 scopus 로고    scopus 로고
    • Mixed memory markov models: Decomposing complex stochastic processes as mixtures of simpler ones
    • Saul, L.K. and Jordan, M.I. 1999. Mixed memory markov models: Decomposing complex stochastic processes as mixtures of simpler ones. Machine Learning, 37:75-87.
    • (1999) Machine Learning , vol.37 , pp. 75-87
    • Saul, L.K.1    Jordan, M.I.2
  • 25
    • 0000860629 scopus 로고    scopus 로고
    • Predicting the future of discrete sequences from fractal representations of the past
    • Tino, P. and Dorffner, G. 2001. Predicting the future of discrete sequences from fractal representations of the past. Machine Learning, 45(2): 187-218.
    • (2001) Machine Learning , vol.45 , Issue.2 , pp. 187-218
    • Tino, P.1    Dorffner, G.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.