Survey on the objectives of recommender systems: Measures, solutions, evaluation methodology, and new perspectives
Recently, recommender systems have played an increasingly important role in a wide
variety of commercial applications to help users find favourite products. Research in the …
variety of commercial applications to help users find favourite products. Research in the …
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, shopping has been a challenging
task. Increased online shopping has increased information available via the World Wide …
task. Increased online shopping has increased information available via the World Wide …
A fuzzy recommendation system for predicting the customers interests using sentiment analysis and ontology in e-commerce
RV Karthik, S Ganapathy - Applied Soft Computing, 2021 - Elsevier
In Electronic commerce, customer reviews play a significant role in purchase making
decision. Most of the existing recommendation systems consider the customer reviews, user …
decision. Most of the existing recommendation systems consider the customer reviews, user …
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 …
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 …
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 …
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 …
An attention-based unsupervised adversarial model for movie review spam detection
With the prevalence of the Internet, online reviews have become a valuable information
resource for people. However, the authenticity of online reviews remains a concern, and …
resource for people. However, the authenticity of online reviews remains a concern, and …
Multi-factor ranking method for trading-off accuracy, diversity, novelty, and coverage of recommender systems
Collaborative filtering (CF) is one of the most popular and commonly used recommendation
methods. Currently, most rating prediction CF methods select top-N recommendations …
methods. Currently, most rating prediction CF methods select top-N recommendations …
Multisample-based contrastive loss for top-k recommendation
Top-k recommendation is a fundamental task in recommendation systems that is generally
learned by comparing positive and negative pairs. The contrastive loss (CL) is the key in …
learned by comparing positive and negative pairs. The contrastive loss (CL) is the key in …