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» Mining Very Large Databases
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KDD
2001
ACM
163views Data Mining» more  KDD 2001»
16 years 3 months ago
The "DGX" distribution for mining massive, skewed data
Skewed distributions appear very often in practice. Unfortunately, the traditional Zipf distribution often fails to model them well. In this paper, we propose a new probability di...
Zhiqiang Bi, Christos Faloutsos, Flip Korn
IDEAS
1999
IEEE
134views Database» more  IDEAS 1999»
15 years 7 months ago
The EyeDB OODBMS
This paper introduces the EYEDB Object Oriented DataBase Management System (OODBMS). EYEDB implements all the standard features of OODBMS, is language oriented, provides a generic...
Eric Viara, Emmanuel Barillot, Guy Vaysseix
224
Voted
GIS
2004
ACM
16 years 4 months ago
A partial join approach for mining co-location patterns
Spatial co-location patterns represent the subsets of events whose instances are frequently located together in geographic space. We identified the computational bottleneck in the...
Jin Soung Yoo, Shashi Shekhar
ICDCS
2002
IEEE
15 years 8 months ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
216
Voted
GIS
2008
ACM
16 years 4 months ago
Pedestrian flow prediction in extensive road networks using biased observational data
In this paper, we discuss an application of spatial data mining to predict pedestrian flow in extensive road networks using a large biased sample. Existing out-of-the-box techniqu...
Michael May, Simon Scheider, Roberto Rösler, ...