In the first experiment , we use an induction algorithm ( Hwa 2001a ) based on the expectation-maximization ( EM ) principle that induces parsers for PLTIGs .
learning probabilistic lexicalized grammars for natural language processing
Rebecca Hwa
4.2.1 An Expectation-Maximization-Based Learner . In the first experiment , we use an induction algorithm ( Hwa 2001a ) based on the expectation-maximization ( EM ) principle that induces parsers for PLTIGs . The algorithm performs heuristic search through an iterative reestimation procedure to find local optima : sets of values for the grammar parameters that maximizes the grammar 's likelihood of generating the training data .
In the first experiment , we use an induction algorithm ( @@CITATIONa ) based on the expectation-maximization ( EM ) principle that induces parsers for PLTIGs .