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Volumn , Issue , 2014, Pages 383-388

Choosing the metric in high-dimensional spaces based on hub analysis

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS; NEAREST NEIGHBOR SEARCH; NEURAL NETWORKS;

EID: 84962013747     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (8)

References (15)
  • 5
    • 84873421776 scopus 로고    scopus 로고
    • Using mutual proximity to improve content-based audio similarity
    • Dominik Schnitzer, Arthur Flexer, Markus Schedl, and Gerhard Widmer. Using mutual proximity to improve content-based audio similarity. In ISMIR, pages 79-84, 2011.
    • (2011) ISMIR , pp. 79-84
    • Schnitzer, D.1    Flexer, A.2    Schedl, M.3    Widmer, G.4
  • 10
    • 84949479246 scopus 로고    scopus 로고
    • On the surprising behavior of distance metrics in high dimensional space
    • Lecture Notes in Computer Science, Springer Berlin/Heidelberg
    • Charu Aggarwal, Alexander Hinneburg, and Daniel Keim. On the surprising behavior of distance metrics in high dimensional space. In Database Theory - ICDT 2001, Lecture Notes in Computer Science, pages 420-434. Springer Berlin/Heidelberg, 2001.
    • (2001) Database Theory - ICDT 2001 , pp. 420-434
    • Aggarwal, C.1    Hinneburg, A.2    Keim, D.3
  • 11
    • 79961076698 scopus 로고    scopus 로고
    • Choosing the metric: A simple model approach
    • volume 358 of Studies in Computational Intelligence. Springer Berlin Heidelberg
    • Damien François, Vincent Wertz, and Michel Verleysen. Choosing the metric: A simple model approach. In Meta-Learning in Computational Intelligence, volume 358 of Studies in Computational Intelligence, pages 97-115. Springer Berlin Heidelberg, 2011.
    • (2011) Meta-Learning in Computational Intelligence , pp. 97-115
    • François, D.1    Wertz, V.2    Verleysen, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.