A long short-term memory deep learning framework for explainable recommendation

H Zarzour, Y Jararweh, MM Hammad… - … on Information and …, 2020‏ - ieeexplore.ieee.org
Due to the growing quantity of information available on the Web, recommender systems
have become crucial component for the success of online shop** stores. However, most …

RecDNNing: a recommender system using deep neural network with user and item embeddings

H Zarzour, ZA Al-Sharif… - 2019 10th International …, 2019‏ - ieeexplore.ieee.org
The success of applying deep learning to many domains has gained strong interest in
develo** new revolutionary recommender systems. However, there are little works …

A personalized reinforcement learning recommendation algorithm using bi-clustering techniques

M Waqar, M Ayub - PloS one, 2025‏ - journals.plos.org
Recommender systems have become a core component of various online platforms, hel**
users get relevant information from the abundant digital data. Traditional RSs often generate …

A learning automata-based approach to improve the scalability of clustering-based recommender systems

S Taghipour, J Akbari Torkestani… - Cybernetics and …, 2024‏ - Taylor & Francis
One of the common techniques to reduce the scalability problem in collaborative filtering
(CF)-based recommender systems is the clustering technique, which accelerates finding the …

An effective model-based trust collaborative filtering for explainable recommendations

H Zarzour, Y Jararweh… - 2020 11th International …, 2020‏ - ieeexplore.ieee.org
Nowadays, many companies through the world wide web like YouTube, Netflix, Aliexpress
and Amazon, provide personalized services as recommendations. Recommender systems …

Mining popular topics from the media

KR Boch, FC Kristjanson, CK Leung… - 2022 IEEE 46th …, 2022‏ - ieeexplore.ieee.org
As we are living in an uncertain world, the uncertainty may have significant and/or direct
implications on various aspects of the computer industry. Hence., innovations of computers …

Using k-means clustering ensemble to improve the performance in recommender systems

H Zarzour, F Maazouzi, M Al-Zinati… - … on Intelligent Data …, 2022‏ - ieeexplore.ieee.org
Collaborative filtering methods are often utilized in the industry of recommender systems.
They work by identifying users with similar tastes and recommending items for each active …

Current trends in english public speech translation (based on TED talks platform)

Y Boyko, Y Kupchyshyna, O Tarasova… - Amazonia …, 2023‏ - mail.amazoniainvestiga.info
Nowadays, the media is rapidly develo**, and messaging processes are inexhaustible
thanks to the Internet. Audiovisual content has become a separate form of communication …

Resource optimisation in cloud computing: comparative study of algorithms applied to recommendations in a big data analysis architecture

A Ndayikengurukiye, A Ez-Zahout… - Journal of Automation …, 2021‏ - yadda.icm.edu.pl
Recommender systems (RS) have emerged as a means of providing relevant content to
users, whether in social networking, health, education, or elections. Furthermore, with the …

Recnn: A deep neural network based recommendation system

S Singh, M Lohakare, K Sayar… - … Conference on Artificial …, 2021‏ - ieeexplore.ieee.org
Deep learning's breakthrough in speech recognition, image analysis and natural language
processing has helped it gain a considerable amount of recognition in today's highly …