Aspect Re-distribution for Learning Better Item Embeddings in Sequential Recommendation
Author:
Affiliation:
1. Zhejiang University, China
2. Shenzhen University, China
Funder
This paper is supported by the National Key R&D Program of China under grant (2022ZD0208605)?and partially supported by the National Natural Science Foundation of China(NSFC) under grant No. 62172283 and No.61672449.
Publisher
ACM
Reference42 articles.
1. Item-based top- N recommendation algorithms
2. Tim Donkers Benedikt Loepp and Jürgen Ziegler. 2017. Sequential user-based recurrent neural network recommendations. In Recsys’17. 152–160. Tim Donkers Benedikt Loepp and Jürgen Ziegler. 2017. Sequential user-based recurrent neural network recommendations. In Recsys’17. 152–160.
3. Simon Dooms Toon De Pessemier and Luc Martens. 2013. MovieTweetings: A movie rating dataset collected from Twitter. In RecSys’13. Simon Dooms Toon De Pessemier and Luc Martens. 2013. MovieTweetings: A movie rating dataset collected from Twitter. In RecSys’13.
4. Magdalini Eirinaki Michalis Vazirgiannis and Dimitris Kapogiannis. 2005. Web path recommendations based on page ranking and Markov models. In WIDM’05. 2–9. Magdalini Eirinaki Michalis Vazirgiannis and Dimitris Kapogiannis. 2005. Web path recommendations based on page ranking and Markov models. In WIDM’05. 2–9.
5. Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In CVPR’16. 770–778. Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In CVPR’16. 770–778.
Cited by 4 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. Contextual MAB Oriented Embedding Denoising for Sequential Recommendation;Proceedings of the 17th ACM International Conference on Web Search and Data Mining;2024-03-04
2. Knowledge-enhanced personalized hierarchical attention network for sequential recommendation;World Wide Web;2024-01
3. Modeling Sequential Collaborative User Behaviors For Seller-Aware Next Basket Recommendation;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21
4. Widespread Flaws in Offline Evaluation of Recommender Systems;Proceedings of the 17th ACM Conference on Recommender Systems;2023-09-14
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