Zobrazeno 1 - 10
of 528
pro vyhledávání: '"Kerrache, A."'
Recommender systems are essential tools in the digital era, providing personalized content to users in areas like e-commerce, entertainment, and social media. Among the many approaches developed to create these systems, latent factor models have prov
Externí odkaz:
http://arxiv.org/abs/2405.18068
Federated Learning (FL) is a decentralized machine learning (ML) technique that allows a number of participants to train an ML model collaboratively without having to share their private local datasets with others. When participants are unmanned aeri
Externí odkaz:
http://arxiv.org/abs/2312.10411
Publikováno v:
ICT Express, Vol 10, Iss 6, Pp 1186-1198 (2024)
Nowadays, the rise in traffic density derived from the population growth in urban areas, has resulted in more traffic congestion. Despite advancements in Intelligent Transportation Systems (ITS), this still remains a considerable challenge. In this s
Externí odkaz:
https://doaj.org/article/0554f8dd3f154dbd857c68556f4c68f9
Autor:
Cheriguene, Youssra, Jaafar, Wael, Kerrache, Chaker Abdelaziz, Yanikomeroglu, Halim, Bousbaa, Fatima Zohra, Lagraa, Nasreddine
Unmanned aerial vehicle (UAV)-enabled edge federated learning (FL) has sparked a rise in research interest as a result of the massive and heterogeneous data collected by UAVs, as well as the privacy concerns related to UAV data transmissions to edge
Externí odkaz:
http://arxiv.org/abs/2308.07273
This paper proposes a sequence-to-sequence learning approach for Arabic pronoun resolution, which explores the effectiveness of using advanced natural language processing (NLP) techniques, specifically Bi-LSTM and the BERT pre-trained Language Model,
Externí odkaz:
http://arxiv.org/abs/2305.11529
Autor:
Abdessamed Echikr, Ali Yachir, Chaker Abdelaziz Kerrache, Abdelkrim Kamel Oudjida, Zakaria Sahraoui
Publikováno v:
Acta Informatica Pragensia, Vol 13, Iss 2, Pp 168-192 (2024)
Integration of the internet of things (IoT) and robotics into the internet of robotic things (IoRT) presents inherent security and trust challenges. This article introduces an innovative blockchain-centred framework designed to address these challeng
Externí odkaz:
https://doaj.org/article/dd6b14f49e37428687a3a6638fd00928
Online stores and service providers rely heavily on recommendation softwares to guide users through the vast amount of available products. Consequently, the field of recommender systems has attracted increased attention from the industry and academia
Externí odkaz:
http://arxiv.org/abs/2210.07814
Recommender systems have become an essential tool for providers and users of online services and goods, especially with the increased use of the Internet to access information and purchase products and services. This work proposes a novel recommendat
Externí odkaz:
http://arxiv.org/abs/2210.07816
Autor:
Kerrache, Said, Benhidour, Hafida
Graph embedding methods aim at finding useful graph representations by mapping nodes to a low-dimensional vector space. It is a task with important downstream applications, such as link prediction, graph reconstruction, data visualization, node class
Externí odkaz:
http://arxiv.org/abs/2209.04884
Complex networks are graphs representing real-life systems that exhibit unique characteristics not found in purely regular or completely random graphs. The study of such systems is vital but challenging due to the complexity of the underlying process
Externí odkaz:
http://arxiv.org/abs/2207.07399