需求驱动的云平台产品关键设计特征识别方法

To improve the product key design knowledge discovery system of cloud service platform and further improve the matching efficiency of requirements and services, a product design key features recognition method based on Bidirectional Encoder Representations from Transformers (BERT) and random Lasso was proposed.First, the user feedback of real products was adopted in the experiment and was annotated manually.Based on BERT model, the output layer was built, and the named entity recognition model in the design field was trained to realize the automatic recognition of explicit design features.Experimental results showed that the proposed method could achieve better performance, precision and recall, and F₁ scores were 90.55%, 97.16% and 93.68% respectively.Simultaneously, a new idea of knowledge transfer was proposed.In the current big data environment, the key design features contained in it could be mined and reused by using random lasso algorithm, so as to realize the accurate positioning of implicit design features.