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» Mining Multiple Large Databases
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GIS
2000
ACM
13 years 7 months ago
A conceptual framework for incorporating cognitive principles into geographical database representation
The advancement of GIS data models to allow the eOEective utilization of very large heterogeneous geographic databases requires a new approach that incorporates models of human cog...
Jeremy L. Mennis, Donna Peuquet, Liujian Qian
ICDE
2012
IEEE
238views Database» more  ICDE 2012»
11 years 10 months ago
Mining Knowledge from Data: An Information Network Analysis Approach
Abstract—Most objects and data in the real world are interconnected, forming complex, heterogeneous but often semistructured information networks. However, many database research...
Jiawei Han, Yizhou Sun, Xifeng Yan, Philip S. Yu
KDD
2004
ACM
207views Data Mining» more  KDD 2004»
14 years 8 months ago
SPIN: mining maximal frequent subgraphs from graph databases
One fundamental challenge for mining recurring subgraphs from semi-structured data sets is the overwhelming abundance of such patterns. In large graph databases, the total number ...
Jun Huan, Wei Wang 0010, Jan Prins, Jiong Yang
KDD
1995
ACM
86views Data Mining» more  KDD 1995»
13 years 11 months ago
Knowledge Discovery from Multiple Databases
Knowledge discovery systemsfor databasesareemployedto provide valuable insights into characteristics and relationshipsthat may exist in the data,but are unknown to the user. This ...
James S. Ribeiro, Kenneth A. Kaufman, Larry Kersch...
ANOR
2010
135views more  ANOR 2010»
13 years 7 months ago
A framework of irregularity enlightenment for data pre-processing in data mining
Abstract Irregularities are widespread in large databases and often lead to erroneous conclusions with respect to data mining and statistical analysis. For example, considerable bi...
Siu-Tong Au, Rong Duan, Siamak G. Hesar, Wei Jiang