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A deep learning based trust-and tag-aware recommender system
Recommender systems are popular tools used in many applications, such as e-commerce, e-
learning, and social networks to help users select their desired items. Collaborative filtering …
learning, and social networks to help users select their desired items. Collaborative filtering …
RDERL: Reliable deep ensemble reinforcement learning-based recommender system
Recommender systems (RSs) have been employed for many real-world applications
including search engines, social networks, and information retrieval systems as powerful …
including search engines, social networks, and information retrieval systems as powerful …
Optimization design of cross border intelligent marketing management model based on multi layer perceptron-grey wolf optimization convolutional neural network
Z Lin, J Yang, Y Lian, Y Chen, Z Huang, K Ning - Scientific Reports, 2025 - nature.com
The cross-border intelligent marketing algorithm based on traditional linear models is
relatively single in information feature extraction, making it difficult to effectively handle …
relatively single in information feature extraction, making it difficult to effectively handle …
A Robust Sequential Recommendation Model Based on Multiple Feedback Behavior Denoising and Trusted Neighbors
H Cai, J Meng, S Yuan, J Ren - Neural Processing Letters, 2024 - Springer
At present, most of the personalized sequential recommendations utilize users' implicit
positive feedback (such as clicks) to predict user behavior, ignoring the impact of implicit …
positive feedback (such as clicks) to predict user behavior, ignoring the impact of implicit …
Toward Sequential Recommendation Model for Long‐Term Interest Memory and Nearest Neighbor Influence
H Cai, J Meng, J Ren, S Yuan - Wireless Communications and …, 2022 - Wiley Online Library
Sequential recommendation can make predictions by fitting users' changing interests based
on the users' continuous historical behavior sequences. Currently, many existing sequential …
on the users' continuous historical behavior sequences. Currently, many existing sequential …
User structural information in priority-based ranking for top-N recommendation
MM Fayezi, AH Golpayegani - Advances in Computational Intelligence, 2023 - Springer
The recommender system is a set of data recovery tools and techniques used to recommend
items to users based on their selection. To improve the accuracy of the recommendation, the …
items to users based on their selection. To improve the accuracy of the recommendation, the …
SIITR: A Semantic Infused Intelligent Approach for Tag Recommendation
In the present-day time, Tag recommendation is of utmost importance as it heads into
annotations and labeling of several entities or elements, be it images or data over the World …
annotations and labeling of several entities or elements, be it images or data over the World …
SIITR: A Semantic Infused Intelligent Approach
M Anirudh, G Deepak… - … and Intelligent Computing …, 2022 - books.google.com
In the present-day time, Tag recommendation is of utmost importance as it heads into
annotations and labeling of several entities or elements, be it images or data over the World …
annotations and labeling of several entities or elements, be it images or data over the World …