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Tamim Mahmud Al-Hasan, Aya Nabil Sayed, Faycal Bensaali, Yassine Himeur, Iraklis Varlamis and George Dimitrakopoulos
Recommender systems are a key technology for many applications, such as e-commerce, streaming media, and social media. Traditional recommender systems rely on collaborative filtering or content-based filtering to make recommendations. However, these appr...
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Hajar Majjate, Youssra Bellarhmouch, Adil Jeghal, Ali Yahyaouy, Hamid Tairi and Khalid Alaoui Zidani
Over the past few decades, the education sector has achieved impressive advancements by incorporating Artificial Intelligence (AI) into the educational environment. Nevertheless, specific educational processes, particularly educational counseling, still ...
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Georgios Chalkiadakis, Ioannis Ziogas, Michail Koutsmanis, Errikos Streviniotis, Costas Panagiotakis and Harris Papadakis
In this paper, we develop a novel hybrid recommender system for the tourism domain, which combines (a) a Bayesian preferences elicitation component which operates by asking the user to rate generic images (corresponding to generic types of POIs) in order...
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Laura Plaza, Lourdes Araujo, Fernando López-Ostenero and Juan Martínez-Romo
Online learning is quickly becoming a popular choice instead of traditional education. One of its key advantages lies in the flexibility it offers, allowing individuals to tailor their learning experiences to their unique schedules and commitments. Moreo...
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Ashish Bagwari, Anurag Sinha, N. K. Singh, Namit Garg and Jyotshana Kanti
Business-based decision support systems have been proposed for a few decades in the e-commerce and textile industries. However, these Decision Support Systems (DSS) have not been so productive in terms of business decision delivery. In our proposed model...
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Olga Malyeyeva, Vadym Yesipov, Roman Artiukh, Viktor Kosenko
Pág. 59 - 68
The subject of research in the article is the methods of finding close objects and technologies of forming recommendations. The aim of the article is to develop a recommendation system based on a hybrid method of searching for objects, taking into accoun...
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Aldo Gordillo, Daniel López-Fernández and Katrien Verbert
Open educational resources (OER) can contribute to democratize education by providing effective learning experiences with lower costs. Nevertheless, the massive amount of resources currently available in OER repositories makes it difficult for teachers a...
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Márcio Guia, Rodrigo Rocha Silva and Jorge Bernardino
The growth of the Internet has increased the amount of data and information available to any person at any time. Recommendation Systems help users find the items that meet their preferences, among the large number of items available. Techniques such as c...
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Vasyl Lytvyn,Victoria Vysotska,Viktor Shatskykh,Ihor Kohut,Oksana Petruchenko,Lyudmyla Dzyubyk,Vitaliy Bobrivetc,Valentyna Panasyuk,Svitlana Sachenko,Myroslav Komar
Pág. 6 - 28
The paper reports a study into recommendation algorithms and determination of their advantages and disadvantages. The method for developing recommendations based on collaborative filtering such as Content-Based Filtering (CBF), Collaborative Filtering (C...
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Elahe Khazaei and Abbas Alimohammadi
Location-based social networking services have attracted great interest with the growth of smart mobile devices. Recommending locations for users based on their preferences is an important task for location-based social networks (LBSNs). Since human bein...
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