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» Scaling Clustering Algorithms to Large Databases
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DMIN
2008
152views Data Mining» more  DMIN 2008»
13 years 10 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
CVPR
2007
IEEE
14 years 10 months ago
City-Scale Location Recognition
We look at the problem of location recognition in a large image dataset using a vocabulary tree. This entails finding the location of a query image in a large dataset containing 3...
Grant Schindler, Matthew Brown, Richard Szeliski
CIKM
2006
Springer
13 years 10 months ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu
CORR
2010
Springer
145views Education» more  CORR 2010»
13 years 8 months ago
Random Indexing K-tree
Random Indexing K-tree is the combination of two algorithms suited for large scale document clustering. Keywords Random Indexing, K-tree, Dimensionality Reduction, B-tree, Search T...
Christopher M. De Vries, Lance De Vine, Shlomo Gev...
GECCO
2008
Springer
182views Optimization» more  GECCO 2008»
13 years 9 months ago
Scaling ant colony optimization with hierarchical reinforcement learning partitioning
This paper merges hierarchical reinforcement learning (HRL) with ant colony optimization (ACO) to produce a HRL ACO algorithm capable of generating solutions for large domains. Th...
Erik J. Dries, Gilbert L. Peterson