An Intelligent Question Answering Platform for Graduate Enrollment

• DOI: 10.5121/csit.2021.111602
• Publication Date: 2021-10-26T08:26:46Z
• Authors: Mengyuan Zhang; Yuting Wang; Jianxia Chen; Yu Cheng
• Keywords: Graduate students

To enhance the competitiveness of colleges and universities in graduate enrollment reduce pressure on candidates for examination consultation, it is necessary practically significant to develop an intelligent Q&A platform, which can understand analyze users' semantics accurately return information they need. However, there are problems such as low volume quality corpus enrollment, this paper develops a question answering platform based novel retrieval model including density-based logistic regression combination convolutional neural networks bidirectional long short-term memory. The experimental results show that proposed effectively alleviate problem data sparseness greatly improve accuracy performance enrollment.