The traditional search engine cannot match the actual information needed by the candidates with searching results when they fill the list of preference in college entrance application, consuming extra energy of them to filter the data, which undoubtedly increase the time cost. We design an intelligent question answering system for academic planning of examinees with the knowledge graph of the college entrance examination, a model for Chinese word segmentation and the Bayesian classification algorithm. Unlike traditional search engines, the artificial intelligence-based question answering system can accurately match the candidates’ questions with search results, reducing the number of repeated searches and data filtering. The test results demonstrate that the system can offer accurate and targeted answers to most of the questions involved in the academic planning.