计算机科学

计算机科学 ›› 2023, Vol. 50 ›› Issue (11A): 220900067-10.doi: 10.11896/jsjkx.220900067

• 大数据&数据科学 • 上一篇    下一篇

一种基于相似学习者判定的个性化学习路径推荐及验证方法

冯舒1,3, 祝义1,2,3, 宋媚1,3, 居程程1,3   

  1. 1 江苏师范大学计算机科学与技术学院 江苏 徐州 221116
    2 南京 航空航天大学高安全系统的软件开发与验证技术工业和信息化部重点实验室 南京 211106
    3 江苏省教育信息化工程技术研究中心 江苏 徐州 221116
  • 发布日期:2023-11-09
  • 通讯作者: 祝义(zhuy@jsnu.edu.cn)
  • 作者简介:(ffeng@jsnu.edu.cn)
  • 基金资助:
    国家自然科学基金(62077029);CCF-华为创新研究计划资助(CCF-HuaweiFM202209);南京航空航天大学基本科研业务费科研基地创新基金(NJ2020022);未来网络科研基金项目(FNSRFP-2021-YB-32);江苏师范大学研究生科研创新计划(2021XKT1384)

Personalized Learning Path Recommendation and Verification Method Based on Similar Learners Determination

FENG Shu1,3, ZHU Yi1,2,3, SONG Mei1,3, JU Chengcheng1,3   

  1. 1 School of Computer Science and Technology,Jiangsu Normal University,Xuzhou,Jiangsu 221116,China
    2 Key Laboratory of Ministry of Industry and Information Technology for Software Development and Verification Technology of High Security Systems,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China
    3 Jiangsu Education Information Engineering Technology Research Center,Xuzhou,Jiangsu 221116,China
  • Published:2023-11-09
  • About author:FENG Shu,born in 1996,postgraduate,is a member of China Computer Federation.Her main research interests include adaptive learning,formal methods and software engineering.
    ZHU Yi,born in 1976,Ph.D,professor,is a member of China Computer Federation.His main research interests include software engineering,formal methods,software reliability,adaptive learning and cyber-physical fusion systems.
  • Supported by:
    National Natural Science Foundation of China(62077029),CCF-Huawei Populus Grove Fund(CCF-HuaweiFM202209),Open Project Fund of Key Laboratory of Safety-Critical Software Ministry of Industry and Information Technology(NJ2020022),Future Network Scientific Research Fund Project(FNSRFP-2021-YB-32) and Graduate Science Research Innovation Program of Jiangsu Normal University(2021XKT1384).

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摘要： 基于相似学习者判定方法由于具有轻量级的特点而被广泛用于个性化推荐领域,目前一般采用协同过滤等机器学习的方法,但此类方法并不能保证判定过程的可解释性以及判定结果的可信性。针对这一问题,提出一种基于相似学习者判定的个性化学习路径推荐及验证方法,采用进程互模拟的方式研究相似学习者的判定过程。首先,扩展CCS(Calculus of Communication System)的行为特性,提出LR-CCS(Learning Resources-Calculus of Communication System),用于建模学习者的学习行为序列;其次,通过进程代数中互模拟理论判定学习者学习行为序列相似性,提出学习行为序列强(弱)互模拟关系判定算法进行互模拟关系判定;再次,使用互模拟验证工具MWB(Mobile Workbench)验证学习者学习行为序列相似性,得到满足互模拟关系的候选推荐路径,以保证判定结果的正确性;最后通过一个基于相似学习者的推荐系统实例验证了该方法的有效性。关键词:学习行为序列相似性;进程代数;CCS;互模拟

关键词: 学习行为序列相似性, 进程代数, CCS, 互模拟

Abstract: The similarity-based learner determination method is widely used in the field of personalized recommendation due to its light weight.At present,machine learning methods such as collaborative filtering are generally used.However,such methods cannot guarantee the interpretability of the determination process and the availability of the determination results.To solve this problem,a personalized learning path recommendation and verification method based on similar learner determination is proposed,which uses the method of process bisimulation to study the determination process of similar learners.Firstly,the behavior characteristics of calculus of communication system(CCS) are extended,and learning resources-calculus of communication system(LR-CCS) is used to model the learning behavior sequence of learners.Secondly,the bisimulation theory of process algebra is used to determine the similarity of learners’ learning behavior sequences,and the algorithms for determining the strong(weak) bisimulation relationship of learning behavior sequence is proposed.Thirdly,the bisimulation verification tool mobile workbench(MWB) is used to verify the similarity of the learner’s learning behavior sequence,and the candidate recommended paths which satisfy the bisimulation relationship are obtained to ensure the correctness of the judgment result.Finally,a case study of a recommender system based on similar learners verifies the effectiveness of this method.

Key words: Similarity of learning behavior sequence, Process algebra, CCS, Bisimulation

中图分类号: 

  • TP311
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