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Combining collaborative filtering and sequential pattern mining for recommendation in e-learning environment

  • Yi Li*
  • , Zhendong Niu
  • , Wei Chen
  • , Wenshi Zhang
  • *此作品的通讯作者
  • Beijing Institute of Technology

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In this paper, we describe a Web log mining approach to recommend learning items for each active learner based on the learner's historical learning track. The proposed method is composed of three parts: discovering content-related item sets by Collaborative Filtering (CF), applying the item sets to Sequential Pattern Mining (SPM) and generating sequential pattern recommendations to learners. Different from other recommendation strategies which use CF or SPM separately, this paper combines the two algorithms together and makes some optimizations to adapt them for E-learning environments. Experiments are conducted for the evaluation of the proposed approach and the results show good performance of it.

源语言英语
主期刊名Advances in Web-Based Learning, ICWL 2011 - 10th International Conference, Proceedings
305-313
页数9
DOI
出版状态已出版 - 2011
活动10th International Conference on Advances in Web-Based Learning, ICWL 2011 - Hong Kong, 中国
期限: 8 12月 201110 12月 2011

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7048 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议10th International Conference on Advances in Web-Based Learning, ICWL 2011
国家/地区中国
Hong Kong
时期8/12/1110/12/11

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