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Volumn 2, Issue , 2006, Pages 736-739

Multi-subset selection for keyword extraction and other prototype search tasks using feature selection algorithms

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE SELECTION ALGORITHMS; KEYWORD EXTRACTION; PROTOTYPE SEARCH;

EID: 34047207840     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2006.832     Document Type: Conference Paper
Times cited : (2)

References (15)
  • 1
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    • Another Move Toward the Minimum Consistent Subset: A Tabu Search Approach to the Condensed Nearest Neighbor Rule
    • JUNE
    • V. Cerverón and F. J. Ferri. Another Move Toward the Minimum Consistent Subset: A Tabu Search Approach to the Condensed Nearest Neighbor Rule IEEE Trans. on Syst., Man, and Cybernetics, 31, 3, JUNE 2001
    • (2001) IEEE Trans. on Syst., Man, and Cybernetics , vol.31 , pp. 3
    • Cerverón, V.1    Ferri, F.J.2
  • 5
    • 84931162639 scopus 로고
    • The condensed nearest neighbor rule
    • May
    • P. E. Hart. The condensed nearest neighbor rule. IEEE Trans. Information Theory, 14, 5, 515-516, May 1968.
    • (1968) IEEE Trans. Information Theory , vol.14 , Issue.5 , pp. 515-516
    • Hart, P.E.1
  • 6
    • 0031078007 scopus 로고    scopus 로고
    • Feature selection: Evaluation, application and small sample performance
    • A. K. Jain and D. Zongker. Feature selection: Evaluation, application and small sample performance. IEEE Transactions on PAMI, 19:153-158, 1997.
    • (1997) IEEE Transactions on PAMI , vol.19 , pp. 153-158
    • Jain, A.K.1    Zongker, D.2
  • 7
    • 0002409860 scopus 로고    scopus 로고
    • A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization
    • T. Joachims. A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization. Proc. Int. Conf. on Machine Learning (ICML), 1997.
    • (1997) Proc. Int. Conf. on Machine Learning (ICML)
    • Joachims, T.1
  • 10
    • 34147149841 scopus 로고    scopus 로고
    • P. Somol and P. Pudil, Oscillating search algorithms for feature selection. In Proc. 15th ICPR, Barcelona, 406-409, 2000.
    • P. Somol and P. Pudil, Oscillating search algorithms for feature selection. In Proc. 15th ICPR, Barcelona, 406-409, 2000.
  • 11
    • 0002442796 scopus 로고    scopus 로고
    • Machine learning in automated text categorization
    • F. Sebastiani. Machine learning in automated text categorization. ACM Computing Surveys, 34:1,1-47, 2002.
    • (2002) ACM Computing Surveys , vol.34 , Issue.1 , pp. 1-47
    • Sebastiani, F.1
  • 12
    • 0003192559 scopus 로고    scopus 로고
    • Multi-Document Summarization: Methodologies and Evaluations
    • Lausanne
    • G.G. Stein, A. Bagga and G. Bowden Wise. Multi-Document Summarization: Methodologies and Evaluations. In: Proc. TALN 2000, Lausanne, 2000.
    • (2000) Proc. TALN
    • Stein, G.G.1    Bagga, A.2    Bowden Wise, G.3
  • 13
    • 9444285495 scopus 로고    scopus 로고
    • Automatic Document Categorization Interpreting the Perfomance of Clustering Algorithms
    • Springer
    • B. Stein and S. Meyer zu Bissen. Automatic Document Categorization Interpreting the Perfomance of Clustering Algorithms LNAI2821, 254-266, Springer, 2003.
    • (2003) LNAI2821 , pp. 254-266
    • Stein, B.1    Meyer zu Bissen, S.2
  • 14
    • 21844478478 scopus 로고    scopus 로고
    • Learning Algorithms for Keyphrase Extraction
    • 2:4, Kluwer
    • P. D. Turney. Learning Algorithms for Keyphrase Extraction. Information Retrieval, 2:4, 303-336, Kluwer, 2000.
    • (2000) Information Retrieval , pp. 303-336
    • Turney, P.D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.