Neighbor Selection for Cold Users in Collaborative Filtering with Positive-Only Feedback
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-00374-6_1
Reference11 articles.
1. Barjasteh, I., Forsati, R., Masrour, F., Esfahanian, A.H., 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, pp. 91–98. ACM, New York (2015). https://doi.org/10.1145/2792838.2800196
2. Bellogín, A., Castells, P., Cantador, I.: Neighbor selection and weighting in user-based collaborative filtering: a performance prediction approach. ACM Trans. Web 8(2), 12:1–12:30 (2014). https://doi.org/10.1145/2579993
3. Dunning, T.: Accurate methods for the statistics of surprise and coincidence. Comput. Linguist. 19(1), 61–74 (1993)
4. Lecture Notes in Business Information Processing;M Enrich,2013
5. Fernández-Tobías, I., Braunhofer, M., Elahi, M., Ricci, F., Cantador, I.: Alleviating the new user problem in collaborative filtering by exploiting personality information. User Model. User-Adap. Inter. 26(2–3), 221–255 (2016). https://doi.org/10.1007/s11257-016-9172-z
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. A Combined Approach For Collaborative Filtering Based Recommender Systems with Matrix Factorisation and Outlier Detection;Journal of Business Analytics;2021-07-03
2. Employing neighborhood reduction for alleviating sparsity and cold start problems in user-based collaborative filtering;Information Retrieval Journal;2020-06-19
3. Alleviating New User Cold-Start in User-Based Collaborative Filtering via Bipartite Network;IEEE Transactions on Computational Social Systems;2020-06
4. Addressing the user cold start with cross-domain collaborative filtering: exploiting item metadata in matrix factorization;User Modeling and User-Adapted Interaction;2019-01-01
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