An intelligent question answering system based on RoBERTa-WWM under home appliance knowledge graph (S)

Recently, the intelligent question answering (QA) system for home appliances has attracted wide attention in China because it can provide users with reasonable suggestions in time.However, the fuzzy boundaries of the Chinese "word groups" and the absence of a unified standard for Chinese question classification result in low efficiency of QA, which has hindered the development of the system for a long time.In this work, we developed a QA model based on RoBERTa-WWM to answer questions about home appliances in specific fields.More importantly, the RoBERTa-WWM-BiLSTM-CRF named entity recognition model and RoBERTa-WWM-TextCNN question semantic classification model were constructed to parse the correct semantics of questions from users, which provided algorithm support for the home appliance QA system.The results showed that the method outperformed baselines, and the QA model showed high interpretability and good performance.