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Volumn 7814 LNCS, Issue , 2013, Pages 784-787

Robust PLSA performs better than LDA

Author keywords

Gibbs sampling; perplexity; robustness; topic modeling

Indexed keywords

DIRICHLET; GENERALIZED LEARNING; GIBBS SAMPLING; PERPLEXITY; PROBABILISTIC TOPIC MODELS; SPARSE SOLUTIONS; TOPIC MODEL; TOPIC MODELING;

EID: 84875474429     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-36973-5_84     Document Type: Conference Paper
Times cited : (15)

References (6)
  • 3
    • 84864054097 scopus 로고    scopus 로고
    • Modeling general and specific aspects of documents with a probabilistic topic model
    • MIT Press
    • Chemudugunta, C., Smyth, P., Steyvers, M.: Modeling general and specific aspects of documents with a probabilistic topic model. In: Advances in Neural Information Processing Systems, vol. 19, pp. 241-248. MIT Press (2006)
    • (2006) Advances in Neural Information Processing Systems , vol.19 , pp. 241-248
    • Chemudugunta, C.1    Smyth, P.2    Steyvers, M.3
  • 4
    • 85026972772 scopus 로고    scopus 로고
    • Probabilistic latent semantic indexing
    • ACM
    • Hofmann, T.: Probabilistic latent semantic indexing. In: 22nd Int'l Conf. SIGIR, pp. 50-57. ACM (1999)
    • (1999) 22nd Int'l Conf. SIGIR , pp. 50-57
    • Hofmann, T.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.