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Volumn , Issue , 2012, Pages 911-926

Extractive multi-document summarization with integer linear programming and support vector regression

Author keywords

Integer linear programming; Support vector regression; Text summarization

Indexed keywords

COMPUTATIONALLY EFFICIENT; INTEGER LINEAR PROGRAMMING; MULTI-DOCUMENT; MULTI-DOCUMENT SUMMARIZATION; STATE OF THE ART; SUPPORT VECTOR REGRESSION (SVR); SUPPORT VECTOR REGRESSION MODELS; TEXT SUMMARIZATION;

EID: 84876798827     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (68)

References (29)
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  • 10
    • 84869660995 scopus 로고    scopus 로고
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    • Vancouver, B.C. Canada
    • Daume, H. and Marcu, D. (2005). Bayesian summarization at DUC and suggestion for extrinsic evaluation. In Proceedings of the Document Understanding Conference, Vancouver, B.C., Canada.
    • (2005) Proceedings of the Document Understanding Conference
    • Daume, H.1    Marcu, D.2
  • 15
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    • Binary codes capable of correcting deletions, insertions, and reversals
    • Levenshtein, V. (1966). Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physice-Doklady, 10(8):707-710.
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    • Levenshtein, V.1
  • 18
    • 84859070008 scopus 로고    scopus 로고
    • A class of submodular functions for document summarization
    • Portland, OR
    • Lin, H. and Bilmes, J. (2011). A class of submodular functions for document summarization. In Proceedings of the 49th Annual Meeting of the ACL-HLT, volume 1, pages 510-520, Portland, OR.
    • (2011) Proceedings of the 49th Annual Meeting of the ACL-HLT , vol.1 , pp. 510-520
    • Lin, H.1    Bilmes, J.2
  • 19
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    • A study of global inference algorithms in multi-document summarization
    • Rome, Italy
    • McDonald, R. (2007). A study of global inference algorithms in multi-document summarization. In Proceedings of the European Conference on Information Retrieval, pages 557-564, Rome, Italy.
    • (2007) Proceedings of the European Conference on Information Retrieval , pp. 557-564
    • McDonald, R.1
  • 26
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    • Support Vector Machine learning for independent and structured output spaces
    • Tsochantaridis, I., Hofmann, T., Joachims, T., and Altun, Y. (2004). Support Vector Machine learning for independent and structured output spaces. Machine Learning Research, 6:1453- 1484.
    • (2004) Machine Learning Research , vol.6 , pp. 1453-1484
    • Tsochantaridis, I.1    Hofmann, T.2    Joachims, T.3    Altun, Y.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.