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Deep learning based recommender system: A survey and new perspectives
With the growing volume of online information, recommender systems have been an
effective strategy to overcome information overload. The utility of recommender systems …
effective strategy to overcome information overload. The utility of recommender systems …
A review on deep learning for recommender systems: challenges and remedies
Recommender systems are effective tools of information filtering that are prevalent due to
increasing access to the Internet, personalization trends, and changing habits of computer …
increasing access to the Internet, personalization trends, and changing habits of computer …
Comparative study of deep learning models for analyzing online restaurant reviews in the era of the COVID-19 pandemic
Y Luo, X Xu - International Journal of Hospitality Management, 2021 - Elsevier
Online reviews remain important during the COVID-19 pandemic as they help customers
make safe dining decisions. To help restaurants better understand customers' needs and …
make safe dining decisions. To help restaurants better understand customers' needs and …
Transnets: Learning to transform for recommendation
R Catherine, W Cohen - Proceedings of the eleventh ACM conference …, 2017 - dl.acm.org
Recently, deep learning methods have been shown to improve the performance of
recommender systems over traditional methods, especially when review text is available …
recommender systems over traditional methods, especially when review text is available …
A multilayered-and-randomized latent factor model for high-dimensional and sparse matrices
How to extract useful knowledge from a high-dimensional and sparse (HiDS) matrix
efficiently is critical for many big data-related applications. A latent factor (LF) model has …
efficiently is critical for many big data-related applications. A latent factor (LF) model has …
Dual learning for explainable recommendation: Towards unifying user preference prediction and review generation
In many recommender systems, users express item opinions through two kinds of behaviors:
giving preferences and writing detailed reviews. As both kinds of behaviors reflect users' …
giving preferences and writing detailed reviews. As both kinds of behaviors reflect users' …
[HTML][HTML] Exploiting deep transformer models in textual review based recommender systems
Textual reviews contain fine-grained information that can effectively infer user preferences
over the items. Accordingly, the latest studies in the field of recommender systems exploit …
over the items. Accordingly, the latest studies in the field of recommender systems exploit …
The state-of-the-art in expert recommendation systems
N Nikzad–Khasmakhi, MA Balafar… - … Applications of Artificial …, 2019 - Elsevier
The recent rapid growth of the Internet content has led to building recommendation systems
that guide users to their needs through an information retrieving process. An expert …
that guide users to their needs through an information retrieving process. An expert …
A novel deep learning model for detection of inconsistency in e-commerce websites
On most e-commerce websites, there are two crucial factors that customers rely on to assess
product quality and dependability: customer reviews provided online and related ratings …
product quality and dependability: customer reviews provided online and related ratings …
Neural text similarity of user reviews for improving collaborative filtering recommender systems
According to the advent of technology and the expansion of using the World Wide Web,
there has been an enormous increase in the number of Internet retailers and their …
there has been an enormous increase in the number of Internet retailers and their …