Content-Based Top-N Recommendation Using Heterogeneous Relations
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-46922-5_24
Reference23 articles.
1. Balabanović, M., Shoham, Y.: Fab: content-based, collaborative recommendation. Comm. ACM 40(3), 66–72 (1997)
2. Barjasteh, I., Forsati, R., Masrour, F., Esfahanian, A., Radha, H.: Cold-start item and user recommendation with decoupled completion and transduction. In: Proceedings of the 9th ACM Conference on Recommender Systems, RecSys 2015, Vienna, Austria, 16–20 September 2015, pp. 91–98 (2015)
3. Chen, Y., Zhao, X., Lin, X., Wang, Y.: Towards frequent subgraph mining on single large uncertain graphs. In: 2015 IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, NJ, USA, 14–17 November 2015, pp. 41–50 (2015)
4. Cheng, Y., Yin, L., Yu, Y.: LorSLIM: low rank sparse linear methods for top-n recommendations. In: 2014 IEEE International Conference on Data Mining, ICDM 2014, Shenzhen, China, 14–17 December 2014, pp. 90–99 (2014)
5. Christakopoulou, E., Karypis, G.: HOSLIM: higher-order sparse linear method for top-n recommender systems. In: Proceedings, Part II Advances in Knowledge Discovery and Data Mining - 18th Pacific-Asia Conference, PAKDD 2014, Tainan, Taiwan, 13–16 May 2014, pp. 38–49 (2014)
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. MOOC Courses Recommendation Algorithm Based on Attention Mechanism Enhanced Graph Convolution Network;Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery;2023
2. Meta-relationship for course recommendation in MOOCs;Multimedia Systems;2022-08-23
3. Embedding ranking-oriented recommender system graphs;Expert Systems with Applications;2021-11
4. Recommendation for MOOC with Learner Neighbors and Learning Series;Web Information Systems Engineering – WISE 2018;2018
5. Forgetting Punished Recommendations for MOOC;Computational Data and Social Networks;2018
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3