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ICDE
2008
IEEE
153views Database» more  ICDE 2008»
14 years 10 months ago
A Framework for Clustering Uncertain Data Streams
Abstract-- In recent years, uncertain data management applications have grown in importance because of the large number of hardware applications which measure data approximately. F...
Charu C. Aggarwal, Philip S. Yu
CIKM
2009
Springer
14 years 3 months ago
Learning to rank from Bayesian decision inference
Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
Jen-Wei Kuo, Pu-Jen Cheng, Hsin-Min Wang
UAI
2003
13 years 10 months ago
Learning Module Networks
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
SIGIR
2005
ACM
14 years 2 months ago
On the collective classification of email "speech acts"
We consider classification of email messages as to whether or not they contain certain “email acts”, such as a request or a commitment. We show that exploiting the sequential ...
Vitor Rocha de Carvalho, William W. Cohen
BMCBI
2010
171views more  BMCBI 2010»
13 years 9 months ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...