Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Benhidour, Hafida"'
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
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:
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
Image captioning is the process of automatically generating a description of an image in natural language. Image captioning is one of the significant challenges in image understanding since it requires not only recognizing salient objects in the imag
Externí odkaz:
http://arxiv.org/abs/2206.07986
Akademický článek
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Akademický článek
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Publikováno v:
International Journal of Simulation: Systems, Science & Technology; 2020, Vol. 21 Issue 2, p1-6, 6p
