Grammatical Inference: Algorithms and Applications: 7th - download pdf or read online

By Dana Angluin (auth.), Georgios Paliouras, Yasubumi Sakakibara (eds.)

ISBN-10: 3540234101

ISBN-13: 9783540234104

ISBN-10: 354030195X

ISBN-13: 9783540301950

This ebook constitutes the refereed lawsuits of the seventh foreign Colloquium on Grammatical Inference, ICGI 2004, held in Athens, Greece in October 2004.

The 20 revised complete papers and eight revised poster papers offered including three invited contributions have been rigorously reviewed and chosen from forty five submissions. the themes of the papers offered variety from theoretical result of studying algorithms to cutting edge purposes of grammatical inference and from studying numerous attention-grabbing sessions of formal grammars to estimations of probabilistic grammars.

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Read or Download Grammatical Inference: Algorithms and Applications: 7th International Colloquium, ICGI 2004, Athens, Greece, October 11-13, 2004. Proceedings PDF

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Additional info for Grammatical Inference: Algorithms and Applications: 7th International Colloquium, ICGI 2004, Athens, Greece, October 11-13, 2004. Proceedings

Example text

Since the data-sets will stay available for some time, we expect these problems to be solved in the near future. The goal of providing an indicative measure of the complexity of grammatical inference problems that can be solved using current state of the art techniques has however been partially achieved. An equation (Equation 1) has been developed that defines the size of a set of context-free grammars that can be constructed from a set of training sentences, such that the target language is guaranteed to be contained in this set of context-free grammars.

Next sentences are generated according to the inferred grammar. The number of these sentences that exist in the target language is then measured. This measure is known as the precision. Recall and precision can then be merged into a single measure known as the F-score. The F-Score is a measure of the similarity between the target and inferred languages. A problem with this technique is that once a test sentence has been used to measure recall it cannot be used to measure recall a second time. This because that test sentence can also be used as an additional training example.

When EDSM merges M1 (the merge with the highest evidence score), merges M2, M3, M4, M5, M6, M7, M9 and M10 become invalid. This means that for the next merge selection procedure only merge M8 is possible, since this is the only merge which is pairwise compatible with M1. On the other hand, S-EDSM proceeds by first re-ordering the merges according to the pairwise compatibility of the merges. Column 3 of table 1 shows how the scores are re-calculated for all the merges. For the time being scores are simply added together.

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Grammatical Inference: Algorithms and Applications: 7th International Colloquium, ICGI 2004, Athens, Greece, October 11-13, 2004. Proceedings by Dana Angluin (auth.), Georgios Paliouras, Yasubumi Sakakibara (eds.)


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