A state-of-the-art survey on recommendation system and prospective extensions
With the new era of the Internet, we have a large amount of data available in the form of
ratings, reviews, graphs, images, etc. However, still, people face difficulty in finding useful …
ratings, reviews, graphs, images, etc. However, still, people face difficulty in finding useful …
Deep learning in hospitality and tourism: a research framework agenda for future research
A Essien, G Chukwukelu - International Journal of Contemporary …, 2022 - emerald.com
Purpose This study aims to provide a systematic review of the existing literature on the
applications of deep learning (DL) in hospitality, tourism and travel as well as an agenda for …
applications of deep learning (DL) in hospitality, tourism and travel as well as an agenda for …
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 …
A deep learning based algorithm for multi-criteria recommender systems
Q Shambour - Knowledge-based systems, 2021 - Elsevier
Recommender systems have become exceptionally widespread in recent years to deal with
the information overload problem by providing personalized recommendations. Multi-criteria …
the information overload problem by providing personalized recommendations. Multi-criteria …
[HTML][HTML] Movie recommendation and sentiment analysis using machine learning
In the modern world, where technology is at the forefront of every industry, there has been
an overload of information and data. Thus, a recommendation system comes in handy to …
an overload of information and data. Thus, a recommendation system comes in handy to …
Deep learning architecture for collaborative filtering recommender systems
J Bobadilla, S Alonso, A Hernando - Applied Sciences, 2020 - mdpi.com
This paper provides an innovative deep learning architecture to improve collaborative
filtering results in recommender systems. It exploits the potential of the reliability concept to …
filtering results in recommender systems. It exploits the potential of the reliability concept to …
Deep multi-graph neural networks with attention fusion for recommendation
Graph neural networks (GNNs), with their promising potential to learn effective graph
representation, have been widely used for recommender systems, in which the given graph …
representation, have been widely used for recommender systems, in which the given graph …
On the current state of deep learning for news recommendation
The exponential outbreak of news articles makes it troublesome for the readers to find,
select and read the most relevant ones and alleviate the resulting information and cognitive …
select and read the most relevant ones and alleviate the resulting information and cognitive …
[Retracted] Method of Ideological and Political Teaching Resources in Universities Based on School‐Enterprise Cooperation Mode
T Xia, MT Ahmad - Mathematical Problems in Engineering, 2022 - Wiley Online Library
The personalized recommendation system influences the recommendation of ideological
and political teaching resources in universities, resulting in a high MAE score. As a result …
and political teaching resources in universities, resulting in a high MAE score. As a result …
SARWAS: Deep ensemble learning techniques for sentiment based recommendation system
Identifying user preferences is a complex operation, which makes its automa-tion
challenging, and existing recommendation systems that rely on one of the parameters …
challenging, and existing recommendation systems that rely on one of the parameters …