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75
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ICDM
2007
IEEE
139views Data Mining» more  ICDM 2007»
15 years 4 months ago
Data Clustering with a Relational Push-Pull Model
We present a new generative model for relational data in which relations between objects can have either a binding or a separating effect. For example, in a group of students sep...
Adam Anthony, Marie desJardins
ACPC
1999
Springer
15 years 2 months ago
Modeling and Scheduling for MPEG-4 Based Video Encoder Using a Cluster of Workstations
In this paper, we first present an Object Composition Petri Nets (OCPN) based model methodology for describing the dynamic behaviour of the multiple video objects and user interac...
Yong He, Ishfaq Ahmad, Ming L. Liou
SSDBM
2000
IEEE
87views Database» more  SSDBM 2000»
15 years 2 months ago
A Tool for Nesting and Clustering Large Objects
In implementations of non-standard database systems, large objects are often embedded within an aggregate of different types, i.e. a tuple. For a given size and access probabilit...
Stefan Dieker, Ralf Hartmut Güting, Miguel Ro...
137
Voted
EDBT
2009
ACM
302views Database» more  EDBT 2009»
15 years 4 months ago
RankClus: integrating clustering with ranking for heterogeneous information network analysis
As information networks become ubiquitous, extracting knowledge from information networks has become an important task. Both ranking and clustering can provide overall views on in...
Yizhou Sun, Jiawei Han, Peixiang Zhao, Zhijun Yin,...
86
Voted
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
15 years 10 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson