Inference of Probabilistic Grammars in Different Rules Systems of Natural Languages

Grammar induction is an important and current area within computational linguistics. The results in induction of string transformation rules can be applied not only in linguistics but in many other pattern recognition tasks. The task of grammar induction belongs in general to NP -hard problems. The paper analyses the main rule types in natural languages and in string transformation systems. The paper focuses on the inference of inflectional rule systems which differs in many aspects from the traditional production rule system of Chomsky grammars. The work compares the main candidate methods on the learning of objective-case in the Hungarian language.