Implemented Domain Model Generation
نویسندگان
چکیده
This technical report describes our statistical method for deriving an initial version of the domain model directly from textual specification written in natural language. The main idea of the method is to exploit the intrinsic relations between textual specifications and their domain models. To do this, an in-depth linguistic analysis on the text using the state-of-the-art NLP tools (based on Stanford CoreNLP and Apache OpenNLP) is employed and then a sequence of statistical classifiers (loglinear Maximum Entropy models) is used to predict the domain model. Applicability of our method is demonstrated on an example by evaluation of classifiers’ prediction performance at each stage of the elicitation pipeline. This work was partially supported by the Grant Agency of the Czech Republic project P103/11/1489 and by the Charles University institutional funding SVV-2012-265312. D3S, Technical Report no. D3S-TR-2013-03 CONTENTS
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