NDLI: Objective evaluation of inferred context-free grammars

Content Provider	IEEE Xplore Digital Library
Author	Smith, T.C. Witten, I.H. Cleary, J. Legg, S.
Copyright Year	1994
Description	Author affiliation: Dept. of Comput. Sci., Waikato Univ., Hamilton, New Zealand (Smith, T.C.; Witten, I.H.; Cleary, J.; Legg, S.)
Abstract	An infinite number of context-free grammars may be inferred from a given training set. The defensibility of any single grammar hinges on the ability to compare that grammar against others in a meaningful way. In keeping with the minimum description length principle, smaller grammars are preferred over larger ones, but only insofar as the small grammar does not over-generalise the language being studied. Furthermore, measures of size must incorporate the grammar's ability to cover sentences of the source language not included in the training set. This paper describes a method for evaluating the quality of context-free grammars according to (i) the complexity of each grammar and (ii) the amount of disambiguation information necessary for much grammar to reproduce the training set. The sum of the two evaluations is used as an objective measure of a grammar's information content. Three grammars are used as examples of this process.
Starting Page	392
Ending Page	396
File Size	347454
Page Count	5
File Format	PDF
ISBN	0780324048
DOI	10.1109/ANZIIS.1994.396995
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-11-29
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mars Convergence Computer science Fasteners Inference mechanisms Gold Inference algorithms
Content Type	Text
Resource Type	Article

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