Grammar Induction

I want to go through the Wikipedia series on Machine Learning and Data mining. Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.

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Grammar induction (or grammatical inference) is the process in machine learning of leaning a formal grammar (usually a collection of re-write rules or productions or alternatively as a finite-state machine or automation of some kind) from a set of observations, thus constructing a model which accounts for the characteristics of the observed objects. More generally, grammatical inference is the branch of machine learning where the instance space consists of discrete combinatorial objects such as strings, trees, and graphs.

Grammatical inference has often been very focused on the problem of learning finite-state machines of various types, since there have been efficient algorithms for this problem since the 1980s. Since the beginning of the century, these approaches have been extended to the problem of inference of context-free grammars and richer formalisms, such as multiple context-free grammars.

The simplest form of learning is where the learning algorithm merely receives a set of examples drawn from the language in question: the aim is to learn the language from examples of it.



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