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» An Iterative Method for Mining Frequent Temporal Patterns
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KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 9 months ago
A bayesian mixture model with linear regression mixing proportions
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...
ICDM
2008
IEEE
127views Data Mining» more  ICDM 2008»
14 years 3 months ago
Word Sense Discovery for Web Information Retrieval
Word meaning disambiguation has always been an important problem in many computer science tasks, such as information retrieval and extraction. One of the problems, faced in automa...
Tomasz Nykiel, Henryk Rybinski
EDBT
2008
ACM
206views Database» more  EDBT 2008»
14 years 8 months ago
Designing an inductive data stream management system: the stream mill experience
There has been much recent interest in on-line data mining. Existing mining algorithms designed for stored data are either not applicable or not effective on data streams, where r...
Hetal Thakkar, Barzan Mozafari, Carlo Zaniolo
ICTAI
2002
IEEE
14 years 1 months ago
Data Mining for Selective Visualization of Large Spatial Datasets
Data mining is the process of extracting implicit, valuable, and interesting information from large sets of data. Visualization is the process of visually exploring data for patte...
Shashi Shekhar, Chang-Tien Lu, Pusheng Zhang, Ruli...
PKDD
2009
Springer
169views Data Mining» more  PKDD 2009»
14 years 3 months ago
Hybrid Least-Squares Algorithms for Approximate Policy Evaluation
The goal of approximate policy evaluation is to “best” represent a target value function according to a specific criterion. Temporal difference methods and Bellman residual m...
Jeffrey Johns, Marek Petrik, Sridhar Mahadevan