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Mean shift, mode seeking, and clustering

by Yizong Cheng - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1995
"... Abstract-Mean shift, a simple iterative procedure that shifts each data point to the average of data points in its neighborhood, is generalized and analyzed in this paper. This generalization makes some k-means like clustering algorithms its special cases. It is shown that mean shift is a mode-seeki ..."
Abstract - Cited by 620 (0 self) - Add to MetaCart
Abstract-Mean shift, a simple iterative procedure that shifts each data point to the average of data points in its neighborhood, is generalized and analyzed in this paper. This generalization makes some k-means like clustering algorithms its special cases. It is shown that mean shift is a mode

Adaptive clustering for mobile wireless networks

by Chunhung Richard Lin, Mario Gerla - IEEE Journal on Selected Areas in Communications , 1997
"... This paper describes a self-organizing, multihop, mobile radio network, which relies on a code division access scheme for multimedia support. In the proposed network architecture, nodes are organized into nonoverlapping clusters. The clusters are independently controlled and are dynamically reconfig ..."
Abstract - Cited by 556 (11 self) - Add to MetaCart
This paper describes a self-organizing, multihop, mobile radio network, which relies on a code division access scheme for multimedia support. In the proposed network architecture, nodes are organized into nonoverlapping clusters. The clusters are independently controlled and are dynamically

CURE: An Efficient Clustering Algorithm for Large Data sets

by Sudipto Guha, Rajeev Rastogi, Kyuseok Shim - Published in the Proceedings of the ACM SIGMOD Conference , 1998
"... Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers. We propose a new clustering ..."
Abstract - Cited by 713 (5 self) - Add to MetaCart
and then shrinking them toward the center of the cluster by a specified fraction. Having more than one representative point per cluster allows CURE to adjust well to the geometry of non-spherical shapes and the shrinking helps to dampen the effects of outliers. To handle large databases, CURE employs a combination

Clustering by passing messages between data points

by Brendan J. Frey, Delbert Dueck - Science , 2007
"... Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars ” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only if that initi ..."
Abstract - Cited by 688 (9 self) - Add to MetaCart
so in less than one-hundredth the amount of time. Clustering data based on a measure of similarity is a critical step in scientific data analysis and in engineering systems. A common approach is to use data to learn a set of centers such that the sum of

Managing Energy and Server Resources in Hosting Centers

by Jeffrey S. Chase, Darrell C. Anderson, Prachi N. Thakar, Amin M. Vahdat - In Proceedings of the 18th ACM Symposium on Operating System Principles (SOSP , 2001
"... Interact hosting centers serve multiple service sites from a common hardware base. This paper presents the design and implementation of an architecture for resource management in a hosting center op-erating system, with an emphasis on energy as a driving resource management issue for large server cl ..."
Abstract - Cited by 558 (37 self) - Add to MetaCart
Interact hosting centers serve multiple service sites from a common hardware base. This paper presents the design and implementation of an architecture for resource management in a hosting center op-erating system, with an emphasis on energy as a driving resource management issue for large server

OPTICS: Ordering Points To Identify the Clustering Structure

by Mihael Ankerst, Markus M. Breunig, Hans-peter Kriegel, Jörg Sander , 1999
"... Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysis and data processing, or as a preprocessing step for other algorithms operating on the detected clusters. Almost all of ..."
Abstract - Cited by 511 (49 self) - Add to MetaCart
Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysis and data processing, or as a preprocessing step for other algorithms operating on the detected clusters. Almost all

Model-Based Clustering, Discriminant Analysis, and Density Estimation

by Chris Fraley, Adrian E. Raftery - JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION , 2000
"... Cluster analysis is the automated search for groups of related observations in a data set. Most clustering done in practice is based largely on heuristic but intuitively reasonable procedures and most clustering methods available in commercial software are also of this type. However, there is little ..."
Abstract - Cited by 557 (28 self) - Add to MetaCart
Cluster analysis is the automated search for groups of related observations in a data set. Most clustering done in practice is based largely on heuristic but intuitively reasonable procedures and most clustering methods available in commercial software are also of this type. However

Database resources of the National Center for Biotechnology Information

by David L. Wheeler, Tanya Barrett, Dennis A. Benson, Stephen H. Bryant, Kathi Canese, Vyacheslav Chetvernin, Deanna M. Church, Michael Dicuccio, Ron Edgar, Scott Federhen, Lewis Y. Geer, Yuri Kapustin, Oleg Khovayko, David L, David J. Lipman, Thomas L. Madden, Donna R. Maglott, James Ostell, Vadim Miller, Kim D. Pruitt, Gregory D. Schuler, Edwin Sequeira, Steven T. Sherry, Karl Sirotkin, Re Souvorov, Grigory Starchenko, Roman L. Tatusov, Tatiana A. Tatusova, Lukas Wagner, Eugene Yaschenko - Nucleic Acids Res , 2008
"... In addition to maintaining the GenBankÒ nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s Web site. NCBI resources include Entrez, ..."
Abstract - Cited by 964 (15 self) - Add to MetaCart
In addition to maintaining the GenBankÒ nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s Web site. NCBI resources include Entrez,

Scatter/Gather: A Cluster-based Approach to Browsing Large Document Collections

by Douglass R. Cutting, David R. Karger, Jan O. Pedersen, John W. Tukey , 1992
"... Document clustering has not been well received as an information retrieval tool. Objections to its use fall into two main categories: first, that clustering is too slow for large corpora (with running time often quadratic in the number of documents); and second, that clustering does not appreciably ..."
Abstract - Cited by 772 (12 self) - Add to MetaCart
Document clustering has not been well received as an information retrieval tool. Objections to its use fall into two main categories: first, that clustering is too slow for large corpora (with running time often quadratic in the number of documents); and second, that clustering does not appreciably

GPFS: A Shared-Disk File System for Large Computing Clusters

by Frank Schmuck, Roger Haskin - In Proceedings of the 2002 Conference on File and Storage Technologies (FAST , 2002
"... GPFS is IBM's parallel, shared-disk file system for cluster computers, available on the RS/6000 SP parallel supercomputer and on Linux clusters. GPFS is used on many of the largest supercomputers in the world. GPFS was built on many of the ideas that were developed in the academic community ove ..."
Abstract - Cited by 518 (3 self) - Add to MetaCart
GPFS is IBM's parallel, shared-disk file system for cluster computers, available on the RS/6000 SP parallel supercomputer and on Linux clusters. GPFS is used on many of the largest supercomputers in the world. GPFS was built on many of the ideas that were developed in the academic community
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