[1]金晶,怀丽波*.基于标签和协同过滤的改进推荐算法研究[J].延边大学学报(自然科学版),2019,(03):234-240.
 JIN Jing,HUAI Libo*.Research on improved recommender algorithmbased tag and collaborative filtering[J].Journal of Yanbian University,2019,(03):234-240.
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基于标签和协同过滤的改进推荐算法研究

参考文献/References:

[1] 黄泽明.基于主题模型的学术论文推荐系统研究[D].辽宁:大连海事大学,2013.
[2] 刘健.基于标签和协同过滤的个性化推荐算法[J].计算机与现代化,2016(2):62-65.
[3] 蔡强,韩东梅,李海生,等.基于标签和协同过滤的个性化资源推荐[J].计算机科学,2014,41(1):69-71.
[4] 郭彩云,王会进.改进的基于标签的协同过滤算法[J].计算机工程与应用,2016,52(8):56-61.
[5] 李昊阳,符云清.基于标签聚类与项目主题的协同过滤推荐算法[J].计算机科学,2018,45(4):247-251.
[6] PITSILIS Georgios, WANG Wei. Harnessing the power of social bookmarking for improving tag -based recommendations[J]. Computers in Human Behavior, 2015,50:239-251.
[7] ZHENG Xiaolin, WANG Menghan, CHEN Chaochao, et al. EXPLORE: EXPLainable item -tag CO-REcommendation[J]. Information Sciences, 2019,474:170-186.
[8] PARRA -SANTANDER D, BRUSILOVSKY P. Improving collaborative filtering in social tagging systems for the recommendation of scientific articles[C]//Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. Piscataway, USA: IEEE, 2010:136-142.
[9] WANG Chong, BLEI D M. Collaborative topic modeling for recommending scientific articles[C]//Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM, 2011:448-456.
[10] 项亮.推荐系统实践[M].北京:人民邮电出版社,2012:108.
[11] 查叶飞.基于可信机制及用户偏好模型的推荐技术的研究与应用[D].南京:东南大学,2015.

相似文献/References:

[1]潘峰,怀丽波*,崔荣一.融合项目属性特征的SVD协同过滤推荐算法研究[J].延边大学学报(自然科学版),2017,(04):334.
 PAN Feng,HUAI Libo*,CUI Rongyi.Research on SVD collaborative filtering recommender algorithm fused items’ attribute feature[J].Journal of Yanbian University,2017,(03):334.

备注/Memo

收稿日期: 2019-07-21
基金项目:吉林省高等教育学会高教科研课题(JGJX2018B34)
*通信作者: 怀丽波(1973—),女,副教授,研究方向为优化理论与方法、数据挖掘.

更新日期/Last Update: 2019-11-20