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Ce Li, Li Wang, Quanzhi Li and Dongxuan Wang
This application mainly detects the visual attention content and handles operation information in the students? IVR video and visualizes the detection information after the detection is completed. Visualization can be displayed in the following three for...
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Liu Yang, Gang Wang and Hongjun Wang
Aligned with global Sustainable Development Goals (SDGs) and multidisciplinary approaches integrating AI with sustainability, this research introduces an innovative AI framework for analyzing Modern French Poetry. It applies feature extraction techniques...
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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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Margarida Mendonça and Álvaro Figueira
As social media (SM) becomes increasingly prevalent, its impact on society is expected to grow accordingly. While SM has brought positive transformations, it has also amplified pre-existing issues such as misinformation, echo chambers, manipulation, and ...
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Aileen C. Benedict and Zbigniew W. Ras
The paper concerns the problem of action-rule extraction when datasets are large. Such rules can be used to construct a knowledge base in a recommendation system. One of the popular approaches to construct action rules in such cases is to partition the d...
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Christos Troussas, Akrivi Krouska, Antonios Koliarakis and Cleo Sgouropoulou
Recommender systems are widely used in various fields, such as e-commerce, entertainment, and education, to provide personalized recommendations to users based on their preferences and/or behavior. ?his paper presents a novel approach to providing custom...
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William Villegas-Ch and Joselin García-Ortiz
In the digital age, the personalization of learning has become a critical priority in education. This article delves into the cutting-edge of educational innovation by exploring the essential role of ontology-based knowledge representation in transformin...
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Olurotimi Oguntola and Steven Simske
This study proposes a framework for a systems engineering-based approach to context-aware personalization, which is applied to e-commerce through the understanding and modeling of user behavior from their interactions with sales channels and media. The f...
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Dionisis Margaris, Costas Vassilakis, Dimitris Spiliotopoulos and Stefanos Ougiaroglou
Collaborative filtering has proved to be one of the most popular and successful rating prediction techniques over the last few years. In collaborative filtering, each rating prediction, concerning a product or a service, is based on the rating values tha...
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Mohd Anuaruddin Bin Ahmadon, Shingo Yamaguchi, Abd Kadir Mahamad and Sharifah Saon
Online services, ambient services, and recommendation systems take user preferences into data processing so that the services can be tailored to the customer?s preferences. Associative rules have been used to capture combinations of frequently preferred ...
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