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MICAI
2005
Springer
14 years 3 months ago
Proximity Searching in High Dimensional Spaces with a Proximity Preserving Order
Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
Edgar Chávez, Karina Figueroa, Gonzalo Nava...
SIGMOD
2000
ACM
165views Database» more  SIGMOD 2000»
14 years 2 months ago
Finding Generalized Projected Clusters In High Dimensional Spaces
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
Charu C. Aggarwal, Philip S. Yu
SIGMOD
2001
ACM
142views Database» more  SIGMOD 2001»
14 years 10 months ago
Outlier Detection for High Dimensional Data
The outlier detection problem has important applications in the eld of fraud detection, network robustness analysis, and intrusion detection. Most such applications are high dimen...
Charu C. Aggarwal, Philip S. Yu
ALENEX
2001
105views Algorithms» more  ALENEX 2001»
13 years 11 months ago
A Probabilistic Spell for the Curse of Dimensionality
Range searches in metric spaces can be very di cult if the space is \high dimensional", i.e. when the histogram of distances has a large mean and a small variance. The so-cal...
Edgar Chávez, Gonzalo Navarro
ICDE
2002
IEEE
164views Database» more  ICDE 2002»
14 years 11 months ago
Towards Meaningful High-Dimensional Nearest Neighbor Search by Human-Computer Interaction
Nearest Neighbor search is an important and widely used problem in a number of important application domains. In many of these domains, the dimensionality of the data representati...
Charu C. Aggarwal