메뉴 건너뛰기




Volumn , Issue , 2012, Pages 729-738

Collective context-aware topic models for entity disambiguation

Author keywords

Entity disambiguation; Topic models

Indexed keywords

CONTEXT-AWARE; DISCRIMINATIVE FEATURES; ENTITY DISAMBIGUATION; HIGH QUALITY; KNOWLEDGE BASE; NON-PARAMETRIC; TOPIC MODEL; UNSTRUCTURED DATA; WIKIPEDIA;

EID: 84860862477     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2187836.2187935     Document Type: Conference Paper
Times cited : (46)

References (30)
  • 3
    • 33745448357 scopus 로고    scopus 로고
    • A latent dirichlet model for unsupervised entity resolution
    • I. Bhattacharya and L. Getoor. A latent dirichlet model for unsupervised entity resolution. In SDM, 2006.
    • (2006) SDM
    • Bhattacharya, I.1    Getoor, L.2
  • 4
    • 0141607824 scopus 로고    scopus 로고
    • Latent dirichlet allocation
    • D. Blei, A. Ng, and M. Jordan. Latent dirichlet allocation. JMLR, 2003.
    • (2003) JMLR
    • Blei, D.1    Ng, A.2    Jordan, M.3
  • 5
    • 55849092655 scopus 로고    scopus 로고
    • A topic model for word sense disambiguation
    • J. Boyd-Graber, D. Blei, and X. Zhu. A topic model for word sense disambiguation. In EMNLP, 2007.
    • (2007) EMNLP
    • Boyd-Graber, J.1    Blei, D.2    Zhu, X.3
  • 7
    • 0000735610 scopus 로고
    • Operations for learning with graphical models
    • W. L. Buntine. Operations for learning with graphical models. JAIR, 1994.
    • (1994) JAIR
    • Buntine, W.L.1
  • 9
    • 80053379324 scopus 로고    scopus 로고
    • Large-scale named entity disambiguation based on wikipedia data
    • S. Cucerzan. Large-scale named entity disambiguation based on Wikipedia data. In EMNLP, 2007.
    • (2007) EMNLP
    • Cucerzan, S.1
  • 12
    • 0021518209 scopus 로고
    • Stochastic relaxation, gibbs distributions, and the bayesian restoration of images
    • S. Geman and D. Geman. Stochastic relaxation, gibbs distributions, and the bayesian restoration of images. PAMI, 1984.
    • (1984) PAMI
    • Geman, S.1    Geman, D.2
  • 15
    • 50249144225 scopus 로고    scopus 로고
    • Parameter estimation for text analysis
    • G. Heinrich. Parameter estimation for text analysis. Technical report, 2005.
    • (2005) Technical Report
    • Heinrich, G.1
  • 17
    • 57449088306 scopus 로고    scopus 로고
    • Wikify! linking documents to encyclopedic knowledge
    • R. Mihalcea and A. Csomai. Wikify! linking documents to encyclopedic knowledge. In CIKM, 2007.
    • (2007) CIKM
    • Mihalcea, R.1    Csomai, A.2
  • 18
    • 67650697165 scopus 로고    scopus 로고
    • Learning to link with wikipedia
    • D. Milne and I. Witten. Learning to link with Wikipedia. In CIKM, 2008.
    • (2008) CIKM
    • Milne, D.1    Witten, I.2
  • 22
    • 34548559277 scopus 로고    scopus 로고
    • Making logistic regression a core data mining tool with tr-irls
    • A. M. Paul Komarek. Making logistic regression a core data mining tool with tr-irls. In ICDM, 2005.
    • (2005) ICDM
    • Komarek, A.M.P.1
  • 25
    • 79957866123 scopus 로고    scopus 로고
    • A latent topic model for complete entity resolution
    • L. Shu, B. Long, and W. Meng. A latent topic model for complete entity resolution. In ICDE, 2009.
    • (2009) ICDE
    • Shu, L.1    Long, B.2    Meng, W.3
  • 27
    • 80052119994 scopus 로고    scopus 로고
    • An architecture for parallel topic models
    • A. Smola and S. Narayanamurthy. An architecture for parallel topic models. In VLDB, 2010.
    • (2010) VLDB
    • Smola, A.1    Narayanamurthy, S.2
  • 29
    • 33749245495 scopus 로고    scopus 로고
    • Topic modeling: Beyond bag of words
    • H. Wallach. Topic modeling: Beyond bag of words. In ICML, 2006.
    • (2006) ICML
    • Wallach, H.1
  • 30
    • 49749087162 scopus 로고    scopus 로고
    • Topical n-grams: Phrase and topic discovery, with an application to information retrieval
    • X. Wang, A. Mccallum, and X. Wei. Topical n-grams: Phrase and topic discovery, with an application to information retrieval. In ICDM, 2007.
    • (2007) ICDM
    • Wang, X.1    McCallum, A.2    Wei, X.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.