A new distance function for prototype based clustering algorithms in high dimensional spaces

Studies in Classification, Data Analysis, and Knowledge Organization

Volumn , Issue , 2013, Pages 371-378

  Winkler, Roland ^a   Klawonn, Frank ^b   Kruse, Rudolf ^c  

^a GERMAN AEROSPACE CENTER DLR   (Germany)

^b UNIVERSITY OF APPLIED SCIENCES   (Germany)

^c OTTO VON GUERICKE UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DATA SET; DISTANCE FUNCTIONS; FEATURE SPACE; HIGH DIMENSIONAL SPACES; HIGH-DIMENSIONAL DATA ANALYSIS; NUMBER OF CLUSTERS; PROTOTYPE-BASED CLUSTERING; SIDE EFFECT;

DATA MINING;

CLUSTERING ALGORITHMS;

EID: 84892606375     PISSN: 14318814     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-319-00032-942     Document Type: Conference Paper

References (8)

1. Beyer, K., Goldstein, J., Ramakrishnan, R., & Shaft, U. (1999). When is nearest neighbor meaningful? In Database theory - ICDT'99, vol.1540 of Lecture notes in computer science (pp. 217-235). Berlin/Heidelberg: Springer.
2. Bezdek, J. C. (1981). Pattern recognition with fuzzy objective function algorithms. New York: Plenum Press.
3. Dave, R. N. (1991). Characterization and detection of noise in clustering. Pattern Recognition Letters, 12(11), 657-664.
4. Dunn, J. C. (1973). A fuzzy relative of the isodata process and its use in detecting compact wellseparated clusters. Cybernetics and Systems: An International Journal, 3(3), 32-57.
5. Durrant, R. J., & Kaban, A. (2008). When is 'nearest neighbour' meaningful: A converse theorem and implications. Journal of Complexity, 25(4), 385-397.
6. Hinneburg, A., Aggarwal, C. C., & Keim, D. A. (2000). What is the nearest neighbor in high dimensional spaces? In VLDB '00: Proceedings of the 26th international conference on very large data bases (pp. 506-515). San Francisco, CA: Morgan Kaufmann Publishers.
7. Hsu, C. -M., & Chen, M. -S. (2009). On the design and applicability of distance functions in high-dimensional data space. IEEE Transactions on Knowledge and Data Engineering, 21(4), 523-536.
8. Winkler, R., Klawonn, F., & Kruse, R. (2011). Fuzzy c-means in high dimensional spaces. IJFSA, 1(1), 1-16.