使用贝叶斯分类的高考学业规划智能问答系统

考生在填报高考志愿时,针对复杂繁多的各类高校信息数据,传统的搜索引擎无法根据考生需要的实际信息和搜索结果进行匹配,考生还需要额外消耗一定精力去筛选数据,这无疑增加了考生的时间成本.为此本文提出了基于高考领域知识图谱,使用中文分词模型和朴素贝叶斯分类算法,设计并开发了针对高考学业规划的智能问答系统.与传统的搜索引擎不同的是,基于人工智能的问答系统能够对考生所关注的问题和搜索结果进行精确匹配,减少考生重复搜索和筛选数据的次数.测试结果表明,本系统可以对高考学业规划中所涉及的大多数问题进行相对准确的针对性回答.

Intelligent Question Answering System for College Entrance Examination Using Bayesian Classification

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.