Extracting Software Requirements from Unstructured Documents

نویسندگان

چکیده

Requirements identification in textual documents or extraction is a tedious and error prone task that many researchers suggest automating. We manually annotated the PURE dataset thus created new one containing both requirements non-requirements. Using this dataset, we fine-tuned BERT model compare results with several baselines such as fastText ELMo. In order to evaluate on semantically more complex experiments Request For Information (RFI) documents. The RFIs often include software requirements, but less standardized way. showed promising binary sentence classification task. Comparing previous recent studies dealing constrained inputs, our approach demonstrates high performance terms of precision recall metrics, while being agnostic unstructured input.

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ژورنال

عنوان ژورنال: Communications in computer and information science

سال: 2022

ISSN: ['1865-0937', '1865-0929']

DOI: https://doi.org/10.1007/978-3-031-15168-2_2