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FLAIRS
2008
13 years 9 months ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar
WWW
2008
ACM
14 years 8 months ago
Learning to classify short and sparse text & web with hidden topics from large-scale data collections
This paper presents a general framework for building classifiers that deal with short and sparse text & Web segments by making the most of hidden topics discovered from larges...
Xuan Hieu Phan, Minh Le Nguyen, Susumu Horiguchi
WWW
2006
ACM
14 years 8 months ago
The web structure of e-government - developing a methodology for quantitative evaluation
In this paper we describe preliminary work that examines whether statistical properties of the structure of websites can be an informative measure of their quality. We aim to deve...
Vaclav Petricek, Tobias Escher, Ingemar J. Cox, He...
VISUALIZATION
2002
IEEE
14 years 9 days ago
Comparative Evaluation of Visualization and Experimental Results Using Image Comparison Metrics
Comparative evaluation of visualization and experiment results is a critical step in computational steering. In this paper, we present a study of image comparison metrics for quan...
Hualin Zhou, Min Chen, Mike F. Webster
ECCV
2004
Springer
14 years 9 months ago
Multiple Classifier System Approach to Model Pruning in Object Recognition
We propose a multiple classifier system approach to object recognition in computer vision. The aim of the approach is to use multiple experts successively to prune the list of cand...
Josef Kittler, Alireza Ahmadyfard