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» Approximate data mining in very large relational data
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KDD
2003
ACM
122views Data Mining» more  KDD 2003»
16 years 2 months ago
Natural communities in large linked networks
We are interested in finding natural communities in largescale linked networks. Our ultimate goal is to track changes over time in such communities. For such temporal tracking, we...
John E. Hopcroft, Omar Khan, Brian Kulis, Bart Sel...
107
Voted
JIIS
2002
130views more  JIIS 2002»
15 years 1 months ago
Image Mining: Trends and Developments
Advances in image acquisition and storage technology have led to tremendous growth in very large and detailed image databases. These images, if analyzed, can reveal useful informa...
Wynne Hsu, Mong-Li Lee, Ji Zhang
EDBT
2009
ACM
113views Database» more  EDBT 2009»
15 years 8 months ago
Type-based categorization of relational attributes
In this work we concentrate on categorization of relational attributes based on their data type. Assuming that attribute type/characteristics are unknown or unidentifiable, we an...
Babak Ahmadi, Marios Hadjieleftheriou, Thomas Seid...
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
16 years 2 months ago
A probabilistic framework for relational clustering
Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
126
Voted
PKDD
2009
Springer
102views Data Mining» more  PKDD 2009»
15 years 8 months ago
Relevance Grounding for Planning in Relational Domains
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
Tobias Lang, Marc Toussaint