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VLDB
1995
ACM
89views Database» more  VLDB 1995»
9 years 10 months ago
OODB Bulk Loading Revisited: The Partitioned-List Approach
Object-oriented and object-relational databases(OODB) need to be able to load the vast quantities of data that OODB users bring to them. Loading OODB datais significantly more com...
Janet L. Wiener, Jeffrey F. Naughton
VLDB
1997
ACM
170views Database» more  VLDB 1997»
9 years 10 months ago
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
A new access method, called M-tree, is proposed to organize and search large data sets from a generic "metric space", i.e. where object proximity is only defined by a di...
Paolo Ciaccia, Marco Patella, Pavel Zezula
PAKDD
2000
ACM
140views Data Mining» more  PAKDD 2000»
9 years 10 months ago
Performance Controlled Data Reduction for Knowledge Discovery in Distributed Databases
The objective of data reduction is to obtain a compact representation of a large data set to facilitate repeated use of non-redundant information with complex and slow learning alg...
Slobodan Vucetic, Zoran Obradovic
ESA
2006
Springer
130views Algorithms» more  ESA 2006»
9 years 10 months ago
Reporting Flock Patterns
Data representing moving objects is rapidly getting more available, especially in the area of wildlife GPS tracking. It is a central belief that information is hidden in large data...
Marc Benkert, Joachim Gudmundsson, Florian Hü...
FGR
2004
IEEE
133views Biometrics» more  FGR 2004»
9 years 10 months ago
Finding Temporal Patterns by Data Decomposition
We present a new unsupervised learning technique for the discovery of temporal clusters in large data sets. Our method performs hierarchical decomposition of the data to find stru...
David C. Minnen, Christopher Richard Wren
GIS
1992
ACM
9 years 11 months ago
Machine Induction of Geospatial Knowledge
Machine learning techniques such as tree induction have become accepted tools for developing generalisations of large data sets, typically for use with production rule systems in p...
Peter A. Whigham, Robert I. McKay, J. R. Davis
VL
1996
IEEE
157views Visual Languages» more  VL 1996»
9 years 11 months ago
Visualizing Program Executions on Large Data Sets
Understanding and interpreting a large data source is an important but challenging operation in many technical disciplines. Computer visualization has become a valuable tool to he...
John T. Stasko, Jeyakumar Muthukumarasamy
SSDBM
1996
IEEE
168views Database» more  SSDBM 1996»
9 years 11 months ago
Data Mining: Machine Learning, Statistics, and Databases
Knowledge discovery in databases and data mining aim at semiautomatic tools for the analysis of large data sets. We give an overview of the area and present someof the research is...
Heikki Mannila
DMKD
1997
ACM
308views Data Mining» more  DMKD 1997»
9 years 11 months ago
A Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining
Partitioning a large set of objects into homogeneous clusters is a fundamental operation in data mining. The k-means algorithm is best suited for implementing this operation becau...
Zhexue Huang
CHI
1997
ACM
9 years 11 months ago
Focus+Context Visualization with Flip Zooming and the Zoom Browser
Flip zooming is a novel focus+context technique for visualizing large data sets. It offers an overview of the data, and gives users instant access to any part. Originally develope...
Lars Erik Holmquist
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