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Volumn 6007 LNCS, Issue , 2010, Pages 149-158

Behavioral analyses of information diffusion models by observed data of social network

Author keywords

[No Author keywords available]

Indexed keywords

BEHAVIORAL ANALYSIS; CONTINUOUS TIME; DIFFUSION PHENOMENA; HIGHLY SENSITIVE; INFORMATION DIFFUSION; OBSERVATION DATA; OBSERVED DATA; PARAMETER LEARNING; PARAMETER VALUES; PROPAGATION SPEED; SOCIAL NETWORKS; USE-MODEL;

EID: 78650368367     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-12079-4_20     Document Type: Conference Paper
Times cited : (42)

References (19)
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    • Goldenberg, J.1    Libai, B.2    Muller, E.3
  • 10
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    • Influence, networks, and public opinion formation
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    • Learning continuous-time information diffusion model for social behavioral data analysis
    • Zhou, Z.-H. Washio, T. (eds.), LNCS, Springer, Heidelberg
    • Saito, K., Kimura, M., Ohara, K., Motoda, H.: Learning continuous-time information diffusion model for social behavioral data analysis. In: Zhou, Z.-H., Washio, T. (eds.) ACML 2009. LNCS, vol. 5828, pp. 322-337. Springer, Heidelberg (2009).
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    • Saito, K.1    Kimura, M.2    Ohara, K.3    Motoda, H.4
  • 15
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    • The enron corpus: A new dataset for email classification research
    • Boulicaut, J.-F. Esposito, F. Giannotti, F. Pedreschi, D. (eds.), LNCS (LNAI), Springer, Heidelberg
    • Klimt, B., Yang, Y.: The enron corpus: A new dataset for email classification research. In: Boulicaut, J.-F., Esposito, F., Giannotti, F., Pedreschi, D. (eds.) ECML 2004. LNCS (LNAI), vol. 3201, pp. 217-226. Springer, Heidelberg (2004).
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.