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- W2779923451 abstract "An end user generally writes down software requirements in ambiguous expressions using natural language; hence, a software developer attuned to programming language finds it difficult to understand th meaning of the requirements. To solve this problem we define semantic categories for disambiguation and classify/annotate the requirement into the categories by using machine-learning models. We extensively use a language frame closely related to such categories for designing features to overcome the problem of insufficient training data compare to the large number of classes. Our proposed model obtained a micro-average F1-score of 0.75, outperforming the previous model, REaCT." @default.
- W2779923451 created "2018-01-05" @default.
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- W2779923451 date "2017-10-30" @default.
- W2779923451 modified "2023-09-27" @default.
- W2779923451 title "Semantic Annotation of Software Requirements with Language Frame" @default.
- W2779923451 doi "https://doi.org/10.21742/ijsesd.2017.4.2.01" @default.
- W2779923451 hasPublicationYear "2017" @default.
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