基于二部图匹配算法的新高考专业历史数据追踪研究  

Research on Historical Data Tracking of New College Entrance Examination Major Based on Bipartite Graph Matching Algorithm

作　　者：孙全亮 吕震宇 SUN Quan-liang;LV Zhen-yu(College of Management,North China University of Science and Technology,Tangshan 063210,China)

机构地区：[1]华北理工大学管理学院,河北唐山063210

出　　处：《电脑与信息技术》2024年第1期109-112,140,共5页Computer and Information Technology

摘　　要：新高考要求按专业填报志愿,精准志愿填报需根据专业历史数据准确预测当年该专业可能的录取分数。针对新高考海量专业录取分数预测过程中,专业名称变化导致的自动历史数据追踪难的问题,设计了一种基于二部图最优匹配的专业历史数据追踪算法。该算法基于编辑距离构建了专业名称相似度测度,使用二部图最优匹配解决了最大相似度匹配导致的多对一匹配问题,强制专业名称前两个汉字相同的匹配规则可避免因字符串包含导致的匹配错误。The new college entrance examination requires applicants to apply according to their major,and accurate applicants should accurately predict the possible admission score of the major in the current year based on the historical data of the major.Aiming at the difficulty of automatic historical data tracking caused by the change of major names in the process of predicting the scores of massive majors in the new college entrance examination,an algorithm based on bipartite graph optimal matching was designed.The similarity measure of major name is constructed based on editing distance,and the problem of many-to-one matching caused by maximum similarity matching is solved by using bipartite graph optimal matching.The matching rule of forcing the first two Chinese characters of major name to be the same can avoid matching errors caused by string inclusion.

关 键 词：新高考 二部图 数据追踪 志愿填报 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]