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CORR
1999
Springer
222views Education» more  CORR 1999»
13 years 5 months ago
Analysis of approximate nearest neighbor searching with clustered point sets
Abstract. Nearest neighbor searching is a fundamental computational problem. A set of n data points is given in real d-dimensional space, and the problem is to preprocess these poi...
Songrit Maneewongvatana, David M. Mount
VLDB
1999
ACM
224views Database» more  VLDB 1999»
13 years 9 months ago
Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering
Many applications require the clustering of large amounts of high-dimensional data. Most clustering algorithms, however, do not work e ectively and e ciently in highdimensional sp...
Alexander Hinneburg, Daniel A. Keim
DMIN
2006
151views Data Mining» more  DMIN 2006»
13 years 6 months ago
Rough Set Theory: Approach for Similarity Measure in Cluster Analysis
- Clustering of data is an important data mining application. One of the problems with traditional partitioning clustering methods is that they partition the data into hard bound n...
Shuchita Upadhyaya, Alka Arora, Rajni Jain
CIKM
2000
Springer
13 years 9 months ago
Vector Approximation based Indexing for Non-uniform High Dimensional Data Sets
With the proliferation of multimedia data, there is increasing need to support the indexing and searching of high dimensional data. Recently, a vector approximation based techniqu...
Hakan Ferhatosmanoglu, Ertem Tuncel, Divyakant Agr...
DMIN
2008
152views Data Mining» more  DMIN 2008»
13 years 6 months ago
PCS: An Efficient Clustering Method for High-Dimensional Data
Clustering algorithms play an important role in data analysis and information retrieval. How to obtain a clustering for a large set of highdimensional data suitable for database ap...
Wei Li 0011, Cindy Chen, Jie Wang