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» Scalable Model-based Clustering by Working on Data Summaries
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ALGORITHMICA
2006
139views more  ALGORITHMICA 2006»
13 years 7 months ago
CONQUEST: A Coarse-Grained Algorithm for Constructing Summaries of Distributed Discrete Datasets
Abstract. In this paper we present a coarse-grained parallel algorithm, CONQUEST, for constructing boundederror summaries of high-dimensional binary attributed data in a distribute...
Jie Chi, Mehmet Koyutürk, Ananth Grama
ICTAI
2009
IEEE
14 years 2 months ago
FlockStream: A Bio-Inspired Algorithm for Clustering Evolving Data Streams
Existing density-based data stream clustering algorithms use a two-phase scheme approach consisting of an online phase, in which raw data is processed to gather summary statistics...
Agostino Forestiero, Clara Pizzuti, Giandomenico S...
IPPS
2000
IEEE
13 years 12 months ago
Scalable Parallel Clustering for Data Mining on Multicomputers
This paper describes the design and implementation on MIMD parallel machines of P-AutoClass, a parallel version of the AutoClass system based upon the Bayesian method for determini...
D. Foti, D. Lipari, Clara Pizzuti, Domenico Talia
MIR
2006
ACM
157views Multimedia» more  MIR 2006»
14 years 1 months ago
Generating summaries and visualization for large collections of geo-referenced photographs
We describe a framework for automatically selecting a summary set of photos from a large collection of geo-referenced photographs. Such large collections are inherently difficult ...
Alexander Jaffe, Mor Naaman, Tamir Tassa, Marc Dav...
KDD
2003
ACM
180views Data Mining» more  KDD 2003»
14 years 7 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han