Ordinal consistency based matrix factorization model for exploiting side information in collaborative filtering-Reference-Cited by-同舟云学术

Ordinal consistency based matrix factorization model for exploiting side information in collaborative filtering

Published:2023-09 Issue: Volume:643 Page:119258
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Pujahari Abinash^ORCID,Sisodia Dilip Singh

Publisher

Elsevier BV

Subject

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

Reference48 articles.

1. The Karush–Kuhn–Tucker (KKT) optimality conditions for fuzzy-valued fractional optimization problems;Agarwal;Math. Comput. Simul.,2023

2. Feature selection method using improved CHI Square on Arabic text classifiers: analysis and application;Alshaer;Multimed. Tools Appl.,2021

3. An automatic clustering technique for query plan recommendation;Azhir;Inf. Sci.,2021

4. Enhancing scalability and accuracy of recommendation systems using unsupervised learning and particle swarm optimization;Bakshi;Appl. Soft Comput.,2014

5. Deep learning and Internet of Things for tourist attraction recommendations in smart cities;Cepeda-Pacheco;Neural Comput. Appl.,2022

Cited by 7 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. Incorporating recklessness to collaborative filtering based recommender systems;Information Sciences;2024-09

3. KGCNA: Knowledge Graph Collaborative Neighbor Awareness Network for Recommendation;IEEE Transactions on Emerging Topics in Computational Intelligence;2024-08

4. Disentangled Cascaded Graph Convolution Networks for Multi-Behavior Recommendation;ACM Transactions on Recommender Systems;2024-07-31

5. On incomplete matrix information completion methods and opinion evolution: Matrix factorization towards adjacency preferences;Engineering Applications of Artificial Intelligence;2024-07