Abstract
A requirement analysis is the basis and source of software system development, and its accuracy, consistency and completeness are the keys to determining software quality. However, at present, most software requirements specifications are prepared manually, which has some problems, such as inconsistency with business description, low preparation efficiency, being error prone and difficulty communicating effectively with business personnel. Aiming at the above problems, this paper realizes a construction model of the software requirements specification graph BiSLTM-CRF-KG by using natural language processing and knowledge graph technology. Simulation experiments on 150 real software system business requirements description corpora show that the BiSLTM-CRF-KG model can obtain 96.31% functional entity recognition accuracy directly from the original corpus, which is better than the classical BiSLTM-CRF, IDCNN-CRF and CRF++ models, and has good performance on different kinds of data sets.
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