In Grammar Induction, what really matters is the data and the relationship between the data and the induced grammar, whereas in Grammatical Inference the actual learning process is what is central and is being examined and measured, not just the result of the process.
GraIn has been emerged as an independent field connecting bioinformatics, computational linguistics, formal language theory, machine learning and pattern recognition. GraIn is a task where the goal is to learn or infer a grammar (or some device that can generate, recognize or describe strings) for a language and from all sorts of information about this language.
[Data and Applications]
Linguistic data: string, tree and graph
Language model learning:
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