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SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
14 years 4 months ago
Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
Fei Wang, Chris H. Q. Ding, Tao Li
ML
2006
ACM
110views Machine Learning» more  ML 2006»
13 years 7 months ago
Distribution-based aggregation for relational learning with identifier attributes
Abstract Identifier attributes--very high-dimensional categorical attributes such as particular product ids or people's names--rarely are incorporated in statistical modeling....
Claudia Perlich, Foster J. Provost
TCSV
2008
202views more  TCSV 2008»
13 years 7 months ago
Probabilistic Object Tracking With Dynamic Attributed Relational Feature Graph
Object tracking is one of the fundamental problems in computer vision and has received considerable attention in the past two decades. The success of a tracking algorithm relies on...
Feng Tang, Hai Tao
EDBT
2009
ACM
102views Database» more  EDBT 2009»
14 years 2 months ago
On keys, foreign keys and nullable attributes in relational mapping systems
We consider the following scenario for a mapping system: given a source schema, a target schema, and a set of value correspondences between these two schemas, generate an executab...
Luca Cabibbo
SIGMOD
2011
ACM
270views Database» more  SIGMOD 2011»
12 years 10 months ago
Automatic discovery of attributes in relational databases
In this work we design algorithms for clustering relational columns into attributes, i.e., for identifying strong relationships between columns based on the common properties and ...
Meihui Zhang, Marios Hadjieleftheriou, Beng Chin O...