文献类型：会议论文

英文题名：A Decision Support Model Used in Teaching Estimation System for Bachelor Course based on RST

作者：Zhao, Rongyong[1];Li, Cuiling[1];Tian, Xiangke[1];Wang, Dong[1];Hu, Qianshan[1];Zhang, Qin[2];Luo, Xiaojuan[3]

机构：[1]Tongji Univ, Coll Elect & Informat Engn, Shanghai 201804, Peoples R China;[2]Shanghai Maritime Univ, Elect Engn & Automat Dept, Shanghai 201306, Peoples R China;[3]East China Univ Sci & Technol, Dept Elect & Commun Engn, Shanghai 200237, Peoples R China

会议论文集：13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

会议日期：JUL 29-31, 2017

会议地点：Guilin, PEOPLES R CHINA

语种：英文

外文关键词：Rough Set Theory; Decision Support Model; Teaching Estimation System

摘要：To build a decision support model used in teaching estimation system(TES) from the viewpoint of knowledge engineering, this paper uses the rough set theory(RST) to discover useful rules from the big data of course materials (books, multi-medias, videos, documents etc.), bachelor student information and responses, teacher information stored in a TES. A heuristic clustering model based on self-organizing mapping is used to map the course references, student and teacher characteristics into conditional attributes, and map student score characteristics into decision attribute respectively. Then both the conditional attributes and decision attributes are discretized into symbolic numbers. Further, a novel decision support model based on rough set theory is built. This model is used for supporting decisions during teaching estimation in the example of bachelor course. Thereby this paper has the important theoretical value and application significance to support the scientific decision used in teaching estimation system for bachelor courses.