This document provides an overview of machine learning techniques for text mining and information extraction, including supervised, unsupervised, and weakly supervised learning algorithms. It discusses support vector machines, naive Bayes models, maximum entropy models, and feature selection methods. Key machine learning approaches covered are support vector machines, naive Bayes classifiers, maximum entropy models, and the use of kernels and feature extraction for text classification tasks.

1. Text Mining, Information and Fact Extraction Part 2: Machine Learning Techniques Marie-Francine Moens Department of Computer Science Katholieke Universiteit Leuven, Belgium [email_address]

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