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Volumn 4362 LNCS, Issue , 2007, Pages 761-770

Multi-document summarization based on cluster using non-negative matrix factorization

Author keywords

[No Author keywords available]

Indexed keywords

DATA PROCESSING; DATABASE SYSTEMS; NOISE ABATEMENT; SEMANTICS;

EID: 38049058211     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-69507-3_66     Document Type: Conference Paper
Times cited : (25)

References (17)
  • 1
    • 38149015849 scopus 로고    scopus 로고
    • Chin-Yew, L.: ROUGE: A Package for Automatic Evaluation of Summaries. In Proceedings of Workshop on Text Summarization Branches Out, Post-Conference Workshop of ACL (2004)
    • Chin-Yew, L.: ROUGE: A Package for Automatic Evaluation of Summaries. In Proceedings of Workshop on Text Summarization Branches Out, Post-Conference Workshop of ACL (2004)
  • 2
    • 0033657466 scopus 로고    scopus 로고
    • Extracting Sentence Segments for Text Summarization: A Machine Learning Approach
    • Chuang, W.T. and Yang, J.: Extracting Sentence Segments for Text Summarization: A Machine Learning Approach. In Proceeding of ACM SIGIR (2000) 152-159
    • (2000) Proceeding of ACM SIGIR , pp. 152-159
    • Chuang, W.T.1    Yang, J.2
  • 4
    • 0034795521 scopus 로고    scopus 로고
    • Generic Text Summarization Using Relevance Measure and Latent Semantic Analysis
    • Gong, Y. and Liu, X.: Generic Text Summarization Using Relevance Measure and Latent Semantic Analysis. In proceeding of ACM SIGIR (2001) 19-25
    • (2001) proceeding of ACM SIGIR , pp. 19-25
    • Gong, Y.1    Liu, X.2
  • 5
    • 38149027454 scopus 로고    scopus 로고
    • Hachey, B., Murray, G., and Reitter, D.: The Embra System at DUC 2005: Query-Oriented Multi-Document Summarization with a Very Large Latent Semantic Space. In Proceedings of the DUC (2005)
    • Hachey, B., Murray, G., and Reitter, D.: The Embra System at DUC 2005: Query-Oriented Multi-Document Summarization with a Very Large Latent Semantic Space. In Proceedings of the DUC (2005)
  • 7
    • 84885651059 scopus 로고    scopus 로고
    • Topic Themes for Multi-Document Summarization
    • Harabagiu, S. and Finley L.: Topic Themes for Multi-Document Summarization. In Proceeding of ACM SIGIR (2005) 202-209
    • (2005) Proceeding of ACM SIGIR , pp. 202-209
    • Harabagiu, S.1    Finley, L.2
  • 9
    • 0033592606 scopus 로고    scopus 로고
    • Learning the Parts of Objects by Non-Negative Matrix Factorization
    • Lee, D.D. and Seung, H.S.: Learning the Parts of Objects by Non-Negative Matrix Factorization. Nature 401 (1999) 788-791
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 11
    • 84880039971 scopus 로고    scopus 로고
    • John Benjamins Publishing Company
    • Mani, I.: Automatic Summarization. John Benjamins Publishing Company (2001)
    • (2001) Automatic Summarization
    • Mani, I.1
  • 13
    • 84887862511 scopus 로고    scopus 로고
    • Introduction to the Special Issue on Summarization
    • Radev, D.R., Hovy, E., and Mckeown, K.: Introduction to the Special Issue on Summarization. Computational Linguistics, volume 28 (2002) 399-408
    • (2002) Computational Linguistics , vol.28 , pp. 399-408
    • Radev, D.R.1    Hovy, E.2    Mckeown, K.3
  • 15
    • 38149127798 scopus 로고    scopus 로고
    • Query-based Multidocument Summarization for Information Retrieval
    • Sakurai, T. and Utsumi, A.: Query-based Multidocument Summarization for Information Retrieval. The Proceeding of NTCIR (2004)
    • (2004) The Proceeding of NTCIR
    • Sakurai, T.1    Utsumi, A.2
  • 16
    • 38049032780 scopus 로고    scopus 로고
    • Topic-Based Summarization at DUC 2005
    • Sassion, H.: Topic-Based Summarization at DUC 2005. In Proceedings of DUC (2005)
    • (2005) Proceedings of DUC
    • Sassion, H.1
  • 17
    • 33745791549 scopus 로고    scopus 로고
    • Structure-Based Query-Specific Document Summarization
    • Varadarajan, R. and Hristidis, V.: Structure-Based Query-Specific Document Summarization. The Proceeding of CIKM (2005) 231-232
    • (2005) The Proceeding of CIKM , pp. 231-232
    • Varadarajan, R.1    Hristidis, V.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.