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ICDM
2007
IEEE
139views Data Mining» more  ICDM 2007»
16 years 1 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
ER
2007
Springer
128views Database» more  ER 2007»
16 years 1 months ago
Dynamic Modeling of Trajectory Patterns using Data Mining and Reverse Engineering
The constant increase of moving object data imposes the need for modeling, processing, and mining trajectories, in order to find and understand the patterns behind these data. Ex...
Luis Otávio Alvares, Vania Bogorny, Jos&eac...
BMCBI
2008
86views more  BMCBI 2008»
15 years 7 months ago
Piecewise multivariate modelling of sequential metabolic profiling data
Background: Modelling the time-related behaviour of biological systems is essential for understanding their dynamic responses to perturbations. In metabolic profiling studies, the...
Mattias Rantalainen, Olivier Cloarec, Timothy M. D...
INFORMATICALT
2002
136views more  INFORMATICALT 2002»
15 years 6 months ago
Comparison of Poisson Mixture Models for Count Data Clusterization
Abstract. Five methods for count data clusterization based on Poisson mixture models are described. Two of them are parametric, the others are semi-parametric. The methods emlploy ...
Jurgis Susinskas, Marijus Radavicius
DBPL
2001
Springer
113views Database» more  DBPL 2001»
15 years 11 months ago
Model-Checking Based Data Retrieval
In this paper we develop a new method for solving queries on semistructured data. The main idea is to see a database as a Kripke Transition System (a model) and a query as a formul...
Agostino Dovier, Elisa Quintarelli