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Volumn , Issue , 2010, Pages 234-241

Information-based models for ad hoc IR

Author keywords

Burstiness; IR theory; Probabilistic models

Indexed keywords

AD HOC IR; BURSTINESS; IR THEORY; MIXTURE MODEL; PROBABILISTIC MODELS;

EID: 77956027389     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1835449.1835490     Document Type: Conference Paper
Times cited : (132)

References (21)
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    • Graph mining: Laws, generators, and algorithms
    • D. Chakrabarti and C. Faloutsos. Graph mining: Laws, generators, and algorithms. ACM Comput. Surv., 38(1):2, 2006.
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    • Chakrabarti, D.1    Faloutsos, C.2
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    • Clustering documents with an exponential-family approximation of the dirichlet compound multinomial distribution
    • W. W. Cohen and A. Moore, editors ACM
    • C. Elkan. Clustering documents with an exponential-family approximation of the dirichlet compound multinomial distribution. In W. W. Cohen and A. Moore, editors, ICML, volume 148 of ACM International Conference Proceeding Series, pages 289-296. ACM, 2006.
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    • Elkan, C.1
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    • Advances in information retrieval
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    • C. Macdonald, I. Ounis, V. Plachouras, I. Ruthven, and R. W. White, editors. Advances in Information Retrieval, 30th European Conference on IR Research, ECIR 2008, Glasgow, UK, March 30-April 3, 2008. Proceedings, volume 4956 of Lecture Notes in Computer Science. Springer, 2008.
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    • A study of smoothing methods for language models applied to information retrieval
    • C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to information retrieval. ACM Trans. Inf. Syst., 22(2):179-214, 2004.
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    • Zhai, C.1    Lafferty, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.