메뉴 건너뛰기




Volumn , Issue , 2013, Pages

Bayesian hierarchical community discovery

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS;

EID: 84899019657     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (22)

References (21)
  • 3
    • 0037062448 scopus 로고    scopus 로고
    • Community structure in social and biological networks
    • M. Girvan and M. E. J. Newman. Community structure in social and biological networks. PNAS, 99:7821-7826, 2002.
    • (2002) PNAS , vol.99 , pp. 7821-7826
    • Girvan, M.1    Newman, M.E.J.2
  • 4
    • 41349117788 scopus 로고    scopus 로고
    • Finding community structure in very large networks
    • A. Clauset, M. E. J. Newman, and C. Moore. Finding community structure in very large networks. Physics Review E, 70, 2004.
    • (2004) Physics Review e , vol.70
    • Clauset, A.1    Newman, M.E.J.2    Moore, C.3
  • 5
    • 34247470526 scopus 로고    scopus 로고
    • Learning systems of concepts with an infinite relational model
    • Charles Kemp, Joshua B. Tenenbaum, Thomas L. Griffiths, Takeshi Yamada, and Naonori Ueda. Learning systems of concepts with an infinite relational model. AAAI, 2006.
    • (2006) AAAI
    • Kemp, C.1    Joshua, B.T.2    Thomas, L.G.3    Yamada, T.4    Ueda, N.5
  • 7
    • 84870691266 scopus 로고    scopus 로고
    • Schmidt. Bayesian community detection
    • Morten Mørup and Mikkel N. Schmidt. Bayesian community detection. Neural Computation, 24:2434-2456, 2012.
    • (2012) Neural Computation , vol.24 , pp. 2434-2456
    • Mørup, M.1    Mikkel, N.2
  • 15
    • 0031495186 scopus 로고    scopus 로고
    • Estimation and prediction for stochastic blockmodels for graphs with latent block structure
    • T. Snijders and K. Nowicki. Estimation and prediction for stochastic blockmodels for graphs with latent block structure. Journal of Classification, 14:75-100, 1997.
    • (1997) Journal of Classification , vol.14 , pp. 75-100
    • Snijders, T.1    Nowicki, K.2
  • 16
    • 45749117949 scopus 로고    scopus 로고
    • Bayesian approach to network modularity
    • Jake M. Hofman and Chris H. Wiggins. Bayesian approach to network modularity. Physical Review Letters, 100(25):258701, 2008.
    • (2008) Physical Review Letters , vol.100 , Issue.25 , pp. 258701
    • Jake, M.H.1    Chris, H.W.2
  • 21


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.