Issues and solutions in deep learning-enabled recommendation systems within the e-commerce field
RJK Almahmood, A Tekerek - Applied Sciences, 2022 - mdpi.com
In recent years, especially with the (COVID-19) pandemic, shop** has been a challenging
task. Increased online shop** has increased information available via the World Wide …
task. Increased online shop** has increased information available via the World Wide …
Personalized long-and short-term preference learning for next POI recommendation
Next POI recommendation has been studied extensively in recent years. The goal is to
recommend next POI for users at specific time given users' historical check-in data …
recommend next POI for users at specific time given users' historical check-in data …
Aspect-based sentiment analysis via multitask learning for online reviews
Aspect based sentiment analysis (ABSA) aims to identify aspect terms in online reviews and
predict their corresponding sentiment polarity. Sentiment analysis poses a challenging fine …
predict their corresponding sentiment polarity. Sentiment analysis poses a challenging fine …
A systematic literature review of recent advances on context-aware recommender systems
P Mateos, A Bellogín - Artificial Intelligence Review, 2025 - Springer
Recommender systems are software mechanisms whose usage is to offer suggestions for
different types of entities like products, services, or contacts that could be useful or …
different types of entities like products, services, or contacts that could be useful or …
Dynamic evolution of multi-graph based collaborative filtering for recommendation systems
The recommendation system is an important and widely used technology in the era of Big
Data. Current methods have fused side information into it to alleviate the sparsity problem …
Data. Current methods have fused side information into it to alleviate the sparsity problem …
Generative label fused network for image–text matching
Although there is a long line of research on bidirectional image–text matching, the problem
remains a challenge due to the well-known semantic gap between visual and textual …
remains a challenge due to the well-known semantic gap between visual and textual …
[HTML][HTML] A modified Bayesian boosting algorithm with weight-guided optimal feature selection for sentiment analysis
Sentiment analysis is crucial in understanding and analyzing public opinions, feedback, and
social media data. In this study, we propose a modified Bayesian Boosting algorithm with …
social media data. In this study, we propose a modified Bayesian Boosting algorithm with …
An analysis of cognitive change in online mental health communities: A textual data analysis based on post replies of support seekers
The replies of people seeking support in online mental health communities can be analyzed
to discover if they feel better after receiving support; feeling better indicates a cognitive …
to discover if they feel better after receiving support; feeling better indicates a cognitive …
Personalized location recommendation by fusing sentimental and spatial context
Internet users would like to obtain interesting location information for a travel. With the rapid
development of social media, many kinds of location recommender systems are proposed in …
development of social media, many kinds of location recommender systems are proposed in …
Ranking-based contrastive loss for recommendation systems
The recommendation system is fundamental technology of the internet industry intended to
solve the information overload problem in the big data era. Top-k recommendation is an …
solve the information overload problem in the big data era. Top-k recommendation is an …