An efficient and accurate recommendation strategy using degree classification criteria for item-based collaborative filtering-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

An efficient and accurate recommendation strategy using degree classification criteria for item-based collaborative filtering

Published:2021-02 Issue: Volume:164 Page:113756
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Guo Junpeng,Deng Jiangzhou,Ran Xun,Wang Yong,Jin Hang

Funder

National Natural Science Foundation of China

MEO Layout Foundation of Humanities and Social Sciences

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference36 articles.

1. A noise correction-based approach to support a recommender system in a highly sparse rating environment;Bag;Decision Support Systems,2019

2. An efficient recommendation generation using relevant Jaccard similarity;Bag;Information Sciences,2019

3. Transforming collaborative filtering into supervised learning;Braida;Expert Systems with Applications,2015

4. A fuzzy approach for natural noise management in group recommender systems;Castro;Expert Systems with Applications,2018

5. On identifying k-nearest neighbors in neighborhood models for efficient and effective collaborative filtering;Chae;Neurocomputing,2018

Cited by 24 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. An interval-valued matrix factorization based trust-aware collaborative filtering algorithm for recommendation systems;Information Sciences;2025-01

2. Broad collaborative filtering with adjusted cosine similarity by fusing matrix completion;Applied Soft Computing;2024-11

3. Data-driven smoothing approaches for interest modeling in recommendation systems;Expert Systems with Applications;2024-09

4. Improving the accuracy and diversity of personalized recommendation through a two-stage neighborhood selection;Information Technology and Management;2024-08-05

5. Improving Recommendation System Accuracy Augmenting User Profile with Matrix Factorization;2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE);2024-05-09

同舟云学术

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