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ECAI
2004
Springer
15 years 7 months ago
Exploiting Association and Correlation Rules - Parameters for Improving the K2 Algorithm
A Bayesian network is an appropriate tool to deal with the uncertainty that is typical of real-life applications. Bayesian network arcs represent statistical dependence between dif...
Evelina Lamma, Fabrizio Riguzzi, Sergio Storari
PRICAI
2004
Springer
15 years 7 months ago
Text Classification Using Belief Augmented Frames
: In this paper we present our work on applying Belief Augmented Frames to the text classification problem. We formulate the problem in two alternative ways, and we evaluate the pe...
Colin Keng-Yan Tan
ROCAI
2004
Springer
15 years 7 months ago
Learning Interestingness Measures in Terminology Extraction. A ROC-based approach
Abstract. In the field of Text Mining, a key phase in data preparation is concerned with the extraction of terms, i.e. collocation of words attached to specific concepts (e.g. Ph...
Mathieu Roche, Jérôme Azé, Yve...
AI
2001
Springer
15 years 6 months ago
Learning Bayesian Belief Network Classifiers: Algorithms and System
Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
Jie Cheng, Russell Greiner
AAAI
2007
15 years 4 months ago
Clustering with Local and Global Regularization
Clustering is an old research topic in data mining and machine learning communities. Most of the traditional clustering methods can be categorized local or global ones. In this pa...
Fei Wang, Changshui Zhang, Tao Li