Towards comprehensive approaches for the rating prediction phase in memory-based collaborative filtering recommender systems-Reference-Cited by-同舟云学术

Towards comprehensive approaches for the rating prediction phase in memory-based collaborative filtering recommender systems

Published:2022-04 Issue: Volume:589 Page:878-910
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Nam Le Nguyen Hoai

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference50 articles.

1. Recommendation system development for fashion retail e-commerce;Hwangbo;Electron. Commer. Res. Appl.,2018

2. Service innovation in e-commerce last-mile delivery: mapping the e-customer journey;Vakulenko;J. Bus. Res.,2019

3. Applying landmarks to enhance memory-based collaborative filtering;Lima;Inf. Sci.,2020

4. Recommender systems: introduction and challenges;Ricci,2015

5. Collaborative filtering embeddings for memory-based recommender systems;Valcarce;Eng. Appl. Artif. Intell.,2019

Cited by 15 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. Exploring the effects of personalized recommendations on student’s motivation and learning achievement in gamified mobile learning framework;Education and Information Technologies;2024-01-29

2. RDPCF: Range-based differentially private user data perturbation for collaborative filtering;Computers & Security;2023-11

3. Ordinal consistency based matrix factorization model for exploiting side information in collaborative filtering;Information Sciences;2023-09

4. KTPGN: Novel event-based group recommendation method considering implicit social trust and knowledge propagation;Information Sciences;2023-09

5. Semantic domain comparison of research keywords by indicator-based fuzzy distances: A new prospect;Information Processing & Management;2023-09