메뉴 건너뛰기




Volumn 42, Issue 2, 2009, Pages 251-271

Dimensionality reduction for similarity search with the Euclidean distance in high-dimensional applications

Author keywords

Dimensionality reduction; High dimensional indexing; Multimedia information retrieval; Similarity search

Indexed keywords

FACE RECOGNITION; INDEXING (OF INFORMATION); INFORMATION RETRIEVAL; INFORMATION SERVICES;

EID: 62249215035     PISSN: 13807501     EISSN: 15737721     Source Type: Journal    
DOI: 10.1007/s11042-008-0243-y     Document Type: Article
Times cited : (9)

References (34)
  • 6
    • 0038670812 scopus 로고    scopus 로고
    • Searching in high-dimensional spaces-index structures for improving the performance of multimedia databases
    • 3
    • C Böhm S Berchtold D Keim 2001 Searching in high-dimensional spaces-index structures for improving the performance of multimedia databases ACM Comput Surv 33 3 322 373
    • (2001) ACM Comput Surv , vol.33 , pp. 322-373
    • Böhm, C.1    Berchtold, S.2    Keim, D.3
  • 7
    • 84993661659 scopus 로고    scopus 로고
    • M-tree: An efficient access method for similarity search in metric spaces
    • Athens, 25-29 August 1997
    • Ciaccia P, Patella M, Zezula P (1997) M-tree: an efficient access method for similarity search in metric spaces. In: Proc int'l. conf. on very large data bases, VLDB, Athens, 25-29 August 1997, pp 426-435
    • (1997) Proc int'L. Conf. on Very Large Data Bases, VLDB , pp. 426-435
    • Ciaccia, P.1    Patella, M.2    Zezula, P.3
  • 9
    • 3042542203 scopus 로고    scopus 로고
    • Dimensionality reduction and similarity computation by inner product approximations
    • 6
    • Ö Egecioglu H Ferhatosmanoglu U Ogras 2004 Dimensionality reduction and similarity computation by inner product approximations IEEE Trans Knowl Data Eng 16 6 714 726
    • (2004) IEEE Trans Knowl Data Eng , vol.16 , pp. 714-726
    • Egecioglu O.̈1    Ferhatosmanoglu, H.2    Ogras, U.3
  • 14
    • 0031162081 scopus 로고    scopus 로고
    • The SR-Tree: An index structure for high-dimensional nearest neighbor queries
    • Tucson, 13-15 May 1997
    • Katayama N, Satoh S (1997) The SR-Tree: an index structure for high-dimensional nearest neighbor queries. In: Proc. int'l. conf. on management of data, ACM SIGMOD, Tucson, 13-15 May 1997, pp 369-380
    • (1997) Proc. int'L. Conf. on Management of Data, ACM SIGMOD , pp. 369-380
    • Katayama, N.1    Satoh, S.2
  • 17
    • 34249762939 scopus 로고
    • The TV-Tree: An index structure for high dimensional data
    • 4
    • K Lin H Jagadish C Faloutsos 1994 The TV-Tree: an index structure for high dimensional data VLDB J 3 4 517 542
    • (1994) VLDB J , vol.3 , pp. 517-542
    • Lin, K.1    Jagadish, H.2    Faloutsos, C.3
  • 18
    • 33745854283 scopus 로고    scopus 로고
    • Riemannian manifold learning for nonlinear dimensionality reduction
    • Graz, 7-13 May 2006
    • Lin T, Zha H, Lee SU (2006) Riemannian manifold learning for nonlinear dimensionality reduction. In: Proc. European conf. on computer vision, Graz, 7-13 May 2006, pp 44-55
    • (2006) Proc. European Conf. on Computer Vision , pp. 44-55
    • Lin, T.1    Zha, H.2    Lee, S.U.3
  • 25
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • ST Roweis LK Saul 2000 Nonlinear dimensionality reduction by locally linear embedding Science 290 2323 2326
    • (2000) Science , vol.290 , pp. 2323-2326
    • Roweis, S.T.1    Saul, L.K.2
  • 28
    • 0034704229 scopus 로고    scopus 로고
    • A global geometric framework for nonlinear dimensionality reduction
    • JB Tenenbaum V De Silva JC Langford 2000 A global geometric framework for nonlinear dimensionality reduction Science 290 2319 2323
    • (2000) Science , vol.290 , pp. 2319-2323
    • Tenenbaum, J.B.1    De Silva, V.2    Langford, J.C.3
  • 29
    • 43149101633 scopus 로고    scopus 로고
    • Persistent clustered main memory index for accelerating k-NN queries on high dimensional datasets
    • 2
    • A Thomasian L Zhang 2008 Persistent clustered main memory index for accelerating k-NN queries on high dimensional datasets Multimed Tools Appl 38 2 253 270
    • (2008) Multimed Tools Appl , vol.38 , pp. 253-270
    • Thomasian, A.1    Zhang, L.2
  • 30
    • 51849154226 scopus 로고    scopus 로고
    • Optimal subspace dimensionality for k-Nearest-neighbor queries on clusterd and dimensionality reduced datasets with SVD
    • 2
    • A Thomasian Y Li L Zhang 2008 Optimal subspace dimensionality for k-Nearest-neighbor queries on clusterd and dimensionality reduced datasets with SVD Multimed Tools Appl 40 2 241 259
    • (2008) Multimed Tools Appl , vol.40 , pp. 241-259
    • Thomasian, A.1    Li, Y.2    Zhang, L.3
  • 31
    • 0000681228 scopus 로고    scopus 로고
    • A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces
    • Weber R, Schek HJ, Blott S (1998) A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces. In: Proc. int'l. conf. on very large data bases, VLDB, pp 194-205
    • (1998) Proc. int'L. Conf. on Very Large Data Bases, VLDB , pp. 194-205
    • Weber, R.1    Schek, H.J.2    Blott, S.3
  • 33
    • 34250785110 scopus 로고    scopus 로고
    • A duality view of spectral methods for dimensionality reduction
    • Xiao L, Sun J, Boyd SP (2006) A duality view of spectral methods for dimensionality reduction. In: ICML2006, pp 1041-1048
    • (2006) ICML2006 , pp. 1041-1048
    • Xiao, L.1    Sun, J.2    Boyd, S.P.3
  • 34
    • 62249131746 scopus 로고    scopus 로고
    • University of California
    • University of California (1999) Corel image features. http://kdd.ics.uci.edu/databases/CorelFeatures/CorelFeatures.html
    • (1999) Corel Image Features


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.