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PCM
2001
Springer
183views Multimedia» more  PCM 2001»
13 years 9 months ago
An Adaptive Index Structure for High-Dimensional Similarity Search
A practical method for creating a high dimensional index structure that adapts to the data distribution and scales well with the database size, is presented. Typical media descrip...
Peng Wu, B. S. Manjunath, Shivkumar Chandrasekaran
ICDM
2002
IEEE
158views Data Mining» more  ICDM 2002»
13 years 9 months ago
Adaptive dimension reduction for clustering high dimensional data
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...
EDBT
2000
ACM
13 years 9 months ago
Dynamically Optimizing High-Dimensional Index Structures
In high-dimensional query processing, the optimization of the logical page-size of index structures is an important research issue. Even very simple query processing techniques suc...
Christian Böhm, Hans-Peter Kriegel
ICDE
1998
IEEE
163views Database» more  ICDE 1998»
14 years 6 months ago
Fast Nearest Neighbor Search in High-Dimensional Space
Similarity search in multimedia databases requires an efficient support of nearest-neighbor search on a large set of high-dimensional points as a basic operation for query process...
Stefan Berchtold, Bernhard Ertl, Daniel A. Keim, H...
SIGMOD
2009
ACM
235views Database» more  SIGMOD 2009»
14 years 5 months ago
Quality and efficiency in high dimensional nearest neighbor search
Nearest neighbor (NN) search in high dimensional space is an important problem in many applications. Ideally, a practical solution (i) should be implementable in a relational data...
Yufei Tao, Ke Yi, Cheng Sheng, Panos Kalnis