On the surprising behavior of distance metrics in high dimensional space

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1973, Issue , 2001, Pages 420-434

  Aggarwal, Charu C ^a   Hinneburg, Alexander ^b   Keim, Daniel A ^b  

^a IBM T J WATSON RESEARCH CENTER   (United States)

^b MARTIN LUTHER UNIVERSITY HALLE WITTENBERG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; INDEXING (OF INFORMATION); NEAREST NEIGHBOR SEARCH;

ALGORITHMIC TECHNIQUES; EUCLIDEAN DISTANCE; FRACTIONAL DISTANCE; HIGH DIMENSIONAL SPACES; HIGH DIMENSIONALITY; HIGH-DIMENSIONAL DATA MININGS; MANHATTAN DISTANCE; SIMILARITY BETWEEN OBJECTS;

K-MEANS CLUSTERING;

EID: 84949479246     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44503-x_27     Document Type: Conference Paper

References (11)

1. Weber R., Schek H.-J., Blott S.: A Quantitative Analysis and Performance Study for Similarity-Search Methods in High-Dimensional Spaces. VLDB Conference Proceedings, 1998.
2. Bennett K. P., Fayyad U., Geiger D.: Density-Based Indexing for Approximate Nearest Neighbor Queries. ACM SIGKDD Conference Proceedings, 1999.
3. Berchtold S., Böhm C., Kriegel H.-P.: The Pyramid Technique: Towards Breaking the Curse of Dimensionality. ACM SIGMOD Conference Proceedings,June 1998.
4. Berchtold S., Bohm C., Keim D., Kriegel H.-P.: A Cost Model for Nearest Neighbor Search in High Dimensional Space. ACM PODS Conference Proceedings, 1997.
5. Berchtold S., Ertl B., Keim D., Kriegel H.-P. Seidl T.: Fast Nearest Neighbor Search in High Dimensional Spaces. ICDE Conference Proceedings, 1998.
6. Beyer K., Goldstein J., Ramakrishnan R., Shaft U.: When is Nearest Neighbors Meaningful? ICDT Conference Proceedings, 1999.
7. Shaft U., Goldstein J., Beyer K.: Nearest Neighbor Query Performance for Unstable Distributions. Technical Report TR 1388, Department of Computer Science, University of Wisconsin at Madison.
8. Guttman, A.: R-Trees: A Dynamic Index Structure for Spatial Searching. ACM SIGMOD Conference Proceedings, 1984.
9. Hinneburg A., Aggarwal C., Keim D.: What is the nearest neighbor in high dimensional spaces? VLDB Conference Proceedings, 2000.
10. Katayama N., Satoh S.: The SR-Tree: An Index Structure for High Dimensional Nearest Neighbor Queries. ACM SIGMOD Conference Proceedings, 1997.
11. Lin K.-I., Jagadish H. V., Faloutsos C.: The TV-tree: An Index Structure for High Dimensional Data. VLDB Journal, Volume 3, Number 4, pages 517-542, 1992.