메뉴 건너뛰기




Volumn , Issue , 2010, Pages 57-80

Utilizing nonnegative matrix factorization for email classification problems

Author keywords

Classification; Latent semantic indexing; Nmf initialization; Nonnegative matrix factorization; Phishing; Spam

Indexed keywords


EID: 79952761867     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470689646.ch4     Document Type: Chapter
Times cited : (14)

References (24)
  • 2
    • 36749071484 scopus 로고    scopus 로고
    • SVD based initialization: A head start for nonnegative matrix factorization
    • Boutsidis C and Gallopoulos E 2008 SVD based initialization: A head start for nonnegative matrix factorization. Pattern Recognition 41(4), 1350-1362.
    • (2008) Pattern Recognition , vol.41 , Issue.4 , pp. 1350-1362
    • Boutsidis, C.1    Gallopoulos, E.2
  • 3
    • 0003710380 scopus 로고    scopus 로고
    • LIBSVM: a library for support vector machines
    • Software available at
    • Chang CC and Lin CJ 2001 LIBSVM: a library for support vector machines. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.
    • (2001)
    • Chang, C.C.1    Lin, C.J.2
  • 4
    • 0034824884 scopus 로고    scopus 로고
    • Concept decompositions for large sparse text data using clustering
    • Dhillon IS and Modha DS 2001 Concept decompositions for large sparse text data using clustering. Machine Learning 42(1), 143-175.
    • (2001) Machine Learning , vol.42 , Issue.1 , pp. 143-175
    • Dhillon, IS.1    Modha, DS.2
  • 6
    • 33751097630 scopus 로고    scopus 로고
    • Fast Monte Carlo algorithms for matrices III: Computing a compressed approximate matrix decomposition
    • Drineas P, Kannan R and Mahoney MW 2004 Fast Monte Carlo algorithms for matrices III: Computing a compressed approximate matrix decomposition. SIAM Journal on Computing 36(1), 184-206.
    • (2004) SIAM Journal on Computing , vol.36 , Issue.1 , pp. 184-206
    • Drineas, P.1    Kannan, R.2    Mahoney, M.W.3
  • 7
    • 67650695614 scopus 로고    scopus 로고
    • E-mail classification for phishing defense
    • ECIR 2009, Toulouse, France, April 6-9, 2009. Proceedings (ed. Boughanem M, Berrut C, Mothe J and Soulé-Dupuy C), vol. 5478 of Lecture Notes in Computer Science. Springer.
    • Gansterer WN and Pölz D 2009 E-mail classification for phishing defense. In Advances in Information Retrieval, 31st European Conference on IR Research, ECIR 2009, Toulouse, France, April 6-9, 2009. Proceedings (ed. Boughanem M, Berrut C, Mothe J and Soulé-Dupuy C), vol. 5478 of Lecture Notes in Computer Science. Springer.
    • (2009) In Advances in Information Retrieval, 31st European Conference on IR Research
    • Gansterer, W.N.1    Pölz, D.2
  • 10
    • 0004168818 scopus 로고    scopus 로고
    • Matrix Computations (Johns Hopkins Studies in Mathematical Sciences)
    • The Johns Hopkins University Press.
    • Golub GH and Van Loan CF 1996 Matrix Computations (Johns Hopkins Studies in Mathematical Sciences). The Johns Hopkins University Press.
    • (1996)
    • Golub, G.H.1    Van Loan, C.F.2
  • 11
    • 0004125042 scopus 로고
    • Factor Analysis 2nd edn
    • Lawrence Erlbaum.
    • Gorsuch RL 1983 Factor Analysis 2nd edn. Lawrence Erlbaum.
    • (1983)
    • Gorsuch, R.L.1
  • 15
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • Lee DD and Seung HS 1999 Learning the parts of objects by non-negative matrix factorization. Nature 401(6755), 788-791.
    • (1999) Nature , vol.401 , Issue.6755 , pp. 788-791
    • Lee, DD.1    Seung, H.S.2
  • 19
    • 0028561099 scopus 로고
    • Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values
    • Paatero P and Tapper U 1994 Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values. Environmetrics 5(2), 111-126.
    • (1994) Environmetrics , vol.5 , Issue.2 , pp. 111-126
    • Paatero, P.1    Tapper, U.2
  • 21
    • 58149520173 scopus 로고    scopus 로고
    • Considerations on parallelizing nonnegative matrix factorization for hyperspectral data unmixing
    • Robila S and Maciak L 2009 Considerations on parallelizing nonnegative matrix factorization for hyperspectral data unmixing. Geoscience and Remote Sensing Letters 6(1), 57-61.
    • (2009) Geoscience and Remote Sensing Letters , vol.6 , Issue.1 , pp. 57-61
    • Robila, S.1    Maciak, L.2
  • 22
    • 3042684732 scopus 로고    scopus 로고
    • Seeding non-negative matrix factorization with the spherical k-means clustering
    • Master's Thesis, University of Colorado.
    • Wild SM 2002 Seeding non-negative matrix factorization with the spherical k-means clustering. Master's Thesis, University of Colorado.
    • (2002)
    • Wild, S.M.1
  • 24
    • 12344317125 scopus 로고    scopus 로고
    • Improving non-negative matrix factorizations through structured initialization
    • Wild SM, Curry JH and Dougherty A 2004 Improving non-negative matrix factorizations through structured initialization. Pattern Recognition 37(11), 2217-2232.
    • (2004) Pattern Recognition , vol.37 , Issue.11 , pp. 2217-2232
    • Wild, S.M.1    Curry, J.H.2    Dougherty, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.