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Volumn 3, Issue , 2014, Pages 133-150

Scam Detection in Twitter

Author keywords

Akaike Information Criterion; Bayesian Information Criterion; Latent Semantic Analysis; Suffix Tree; Unlabeled Data

Indexed keywords

CLASSIFICATION (OF INFORMATION); SOCIAL NETWORKING (ONLINE); TREES (MATHEMATICS);

EID: 84943162287     PISSN: 21976503     EISSN: 21976511     Source Type: Book Series    
DOI: 10.1007/978-3-642-45252-9_9     Document Type: Chapter
Times cited : (14)

References (13)
  • 1
    • 85132933917 scopus 로고    scopus 로고
    • Pampapathi, R., Mirkin, B., Levene, M.: A suffix tree approach to anti-spam email filtering. Mach. Learn. 65(1), 309–338 (2006). (Kluwer Academic Publishers)
    • Pampapathi, R., Mirkin, B., Levene, M.: A suffix tree approach to anti-spam email filtering. Mach. Learn. 65(1), 309–338 (2006). (Kluwer Academic Publishers)
  • 8
    • 84860848692 scopus 로고    scopus 로고
    • Overcoming spammers in twitter-a tale of five algorithms
    • Madrid, Espana, pp
    • Gayo-Avello, D., Brenes, D.J.: Overcoming spammers in twitter-a tale of five algorithms. In: Proceedings of the CERI 2010, Madrid, Espana, pp. 41–52 (2010)
    • (2010) Proceedings of the CERI 2010 , pp. 41-52
    • Gayo-Avello, D.1    Brenes, D.J.2
  • 10
    • 33750027607 scopus 로고    scopus 로고
    • Semi-Supervised Text Classification Using EM
    • Chapelle, O., Zien, A., Scholkopf, B. (eds.), MIT Press, Boston
    • Nigam, K., McCallum, A., Mitchell, T.M.: Semi-Supervised Text Classification Using EM. In: Chapelle, O., Zien, A., Scholkopf, B. (eds.) Semi-Supervised Learning. MIT Press, Boston (2006)
    • (2006) Semi-Supervised Learning
    • Nigam, K.1    McCallum, A.2    Mitchell, T.M.3
  • 11
    • 33745456231 scopus 로고    scopus 로고
    • Semi-Supervised Learning Literature Survey
    • University of Wisconsin, Madison
    • Zhu, X.: Semi-Supervised Learning Literature Survey, Computer Sciences Technical Report 1530. University of Wisconsin, Madison (2006)
    • (2006) Computer Sciences Technical Report , vol.1530
    • Zhu, X.1
  • 13
    • 0032269108 scopus 로고    scopus 로고
    • How many clusters? Which clustering method? Answers via model-based cluster analysis
    • Fraley, C., Raftery, A.E.: How many clusters? Which clustering method? Answers via model-based cluster analysis. Comput. J. 41, 578–588 (1998)
    • (1998) Comput. J. , vol.41 , pp. 578-588
    • Fraley, C.1    Raftery, A.E.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.