Collaborative filtering and kNN based recommendation to overcome cold start and sparsity issues: A comparative analysis
Collaborative Filtering (CF) has intrigued several researchers whose goal is to enhance
Recommender System's performance by mitigating their drawbacks. CF's common idea is to …
Recommender System's performance by mitigating their drawbacks. CF's common idea is to …
Collaborative filtering with temporal features for movie recommendation system
Nowadays, recommender systems play a vital role in every human being's life due to the
time retrieving the items. The matrix factorization (MF) technique is one of the main methods …
time retrieving the items. The matrix factorization (MF) technique is one of the main methods …
[HTML][HTML] How can we use artificial intelligence for stock recommendation and risk management? A proposed decision support system
RMD Gonzales, CA Hargreaves - International Journal of Information …, 2022 - Elsevier
Background Decision-making in the stock market is convoluted as it requires significant
trading experience and knowledge. Faced with a huge range of stocks, investors in the stock …
trading experience and knowledge. Faced with a huge range of stocks, investors in the stock …
[HTML][HTML] Dynamic multi-objective sequence-wise recommendation framework via deep reinforcement learning
X Zhang, Y Shang, Y Ren, K Liang - Complex & Intelligent Systems, 2023 - Springer
Sequence-wise recommendation, where recommend exercises to each student step by step,
is one of the most exciting tasks in the field of intelligent tutoring systems (ITS). It is important …
is one of the most exciting tasks in the field of intelligent tutoring systems (ITS). It is important …
Library book recommendation with CNN-FM deep learning approach
X Shi, C Hao, D Yue, H Lu - Library Hi Tech, 2023 - emerald.com
Purpose Traditional library book recommendation methods are mainly based on association
rules and user profiles. They may help to learn about students' interest in different types of …
rules and user profiles. They may help to learn about students' interest in different types of …
A Spatio-Temporal Perspective on Commercial Vehicle Travel Patterns in Urban Environments
J Qin, Y Lin, T Wu, X Lin, X Li - IEEE Access, 2024 - ieeexplore.ieee.org
The relationship between commercial vehicle travel patterns and urban functional areas
reveals potential connections between urban form and human geographic flows, which …
reveals potential connections between urban form and human geographic flows, which …
Video recommendation using social network analysis and user viewing patterns
M Maghsoudi, MH Zohdi - arXiv preprint arXiv:2308.12743, 2023 - arxiv.org
This study proposes a novel video recommendation approach that leverages implicit user
feedback in the form of viewing percentages and social network analysis techniques. By …
feedback in the form of viewing percentages and social network analysis techniques. By …
Hybrid collaborative filtering using matrix factorization and XGBoost for movie recommendation
Nowadays, e-commerce platforms, such as Amazon, Flipkart, Netflix and YouTube,
extensively use recommender systems (RS) techniques. Collaborative filtering (CF) is used …
extensively use recommender systems (RS) techniques. Collaborative filtering (CF) is used …
CDRec-CAS: cross-domain recommendation using context-aware sequences
Recommender Systems (RSs) are a subclass of information filtering systems. RSs assist
users in choosing interesting items from an extensive collection of items. This article …
users in choosing interesting items from an extensive collection of items. This article …
Stacked Noise Reduction Auto Encoder–OCEAN: A Novel Personalized Recommendation Model Enhanced
With the continuous development of information technology and the rapid increase in new
users of social networking sites, recommendation technology is becoming more and more …
users of social networking sites, recommendation technology is becoming more and more …