Optimal algorithms for approximate clustering
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
New techniques for best-match retrieval
ACM Transactions on Information Systems (TOIS)
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
Farthest neighbors, maximum spanning trees and related problems in higher dimensions
Computational Geometry: Theory and Applications
Parallel algorithms for hierarchical clustering
Parallel Computing
Approximation schemes for covering and packing problems in image processing and VLSI
Journal of the ACM (JACM)
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Nearest neighbor queries in metric spaces
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
CURE: an efficient clustering algorithm for large databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Automatic subspace clustering of high dimensional data for data mining applications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Multicluster, mobile, multimedia radio network
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Sublinear time algorithms for metric space problems
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Data structures and algorithms for nearest neighbor search in general metric spaces
SODA '93 Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms
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Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
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ACM Transactions on Database Systems (TODS)
The choice of reference points in best-match file searching
Communications of the ACM
Some approaches to best-match file searching
Communications of the ACM
A practical approach for computing the diameter of a point set
SCG '01 Proceedings of the seventeenth annual symposium on Computational geometry
ACM Computing Surveys (CSUR)
R-tree-based data migration and self-tuning strategies in shared-nothing spatial databases
Proceedings of the 9th ACM international symposium on Advances in geographic information systems
A Fast Parallel Clustering Algorithm for Large Spatial Databases
Data Mining and Knowledge Discovery
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SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
On Clustering Validation Techniques
Journal of Intelligent Information Systems
CLARANS: A Method for Clustering Objects for Spatial Data Mining
IEEE Transactions on Knowledge and Data Engineering
Declustering Spatial Databases on a Multi-Computer Architecture
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Slim-Trees: High Performance Metric Trees Minimizing Overlap Between Nodes
EDBT '00 Proceedings of the 7th International Conference on Extending Database Technology: Advances in Database Technology
When Is ''Nearest Neighbor'' Meaningful?
ICDT '99 Proceedings of the 7th International Conference on Database Theory
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Near Neighbor Search in Large Metric Spaces
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Data Structures and Efficient Algorithms, Final Report on the DFG Special Joint Initiative
Proximity Matching Using Fixed-Queries Trees
CPM '94 Proceedings of the 5th Annual Symposium on Combinatorial Pattern Matching
A Data-Clustering Algorithm on Distributed Memory Multiprocessors
Revised Papers from Large-Scale Parallel Data Mining, Workshop on Large-Scale Parallel KDD Systems, SIGKDD
An Efficient Algorithm for the Approximate Median Selection Problem
CIAC '00 Proceedings of the 4th Italian Conference on Algorithms and Complexity
WaveCluster: a wavelet-based clustering approach for spatial data in very large databases
The VLDB Journal — The International Journal on Very Large Data Bases
Dynamic vp-tree indexing for n-nearest neighbor search given pair-wise distances
The VLDB Journal — The International Journal on Very Large Data Bases
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The VLDB Journal — The International Journal on Very Large Data Bases
Parallel R-Tree Spatial Join for a Shared-Nothing Architecture
DANTE '99 Proceedings of the 1999 International Symposium on Database Applications in Non-Traditional Environments
An Effective Clustering Algorithm to Index High Dimensional Metric Spaces
SPIRE '00 Proceedings of the Seventh International Symposium on String Processing Information Retrieval (SPIRE'00)
Master-Client R-Trees: A New Parallel R-Tree Architecture
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
Clustering Large Datasets in Arbitrary Metric Spaces
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Distributed Clustering for Ad Hoc Networks
ISPAN '99 Proceedings of the 1999 International Symposium on Parallel Architectures, Algorithms and Networks
Geometric techniques for clustering: theory and practice
Geometric techniques for clustering: theory and practice
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Privacy-preserving k-means clustering over vertically partitioned data
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Antipole Tree Indexing to Support Range Search and K-Nearest Neighbor Search in Metric Spaces
IEEE Transactions on Knowledge and Data Engineering
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PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
An Efficient Approximate Algorithm for the 1-Median Problem in Metric Spaces
SIAM Journal on Optimization
Data-Parallel Spatial Join Algorithms
ICPP '94 Proceedings of the 1994 International Conference on Parallel Processing - Volume 03
A Data Structure and an Algorithm for the Nearest Point Problem
IEEE Transactions on Software Engineering
Distributed clustering based on sampling local density estimates
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
WEA'05 Proceedings of the 4th international conference on Experimental and Efficient Algorithms
Adaptive clustering for mobile wireless networks
IEEE Journal on Selected Areas in Communications
A mobility-based framework for adaptive clustering in wireless ad hoc networks
IEEE Journal on Selected Areas in Communications
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In this paper a simple and efficient distributed version of the recently introduced Antipole Clustering algorithm for general metric spaces is proposed. This combines ideas from the M-Tree, the Multi-Vantage Point structure and the FQ-Tree to create a new structure in the "bisector tree" class, called the Antipole Tree. Bisection is based on the proximity to an "Antipole" pair of elements generated by a suitable linear randomized tournament. The final winners (A;B) of such a tournament are far enough apart to approximate the diameter of the splitting set. A simple linear algorithm computing Antipoles in Euclidean spaces with exponentially small approximation ratio is proposed. The Antipole Tree Clustering has been shown to be very effective in important applications such as range and k-nearest neighbor searching, mobile objects clustering in centralized wireless networks with movable base stations and multiple alignment of biological sequences. In many of such applications an efficient distributed clustering algorithm is needed. In the proposed distributed versions of Antipole Clustering the amount of data passed from one node to another is either constant or proportional to the number of nodes in the network. The Distributed Antipole Tree is equipped with additional information in order to perform efficient range search and dynamic clusters management. This is achieved by adding to the randomized tournaments technique, methodologies taken from established systems such as BFR and BIRCH*. Experiments show the good performance of the proposed algorithms on both real and synthetic data.