Resumen Los Sistemas de Recomendación (SR) son técnicas de filtrado de información
que nacen con el objetivo de facilitar o asistir al usuario en la toma de una decisión. El …

In recent years, especially with the (COVID-19) pandemic, shopping has been a challenging
task. Increased online shopping has increased information available via the World Wide …

Sentiment analysis is the computational study of people's opinions, sentiments, emotions,
moods, and attitudes. This fascinating problem offers numerous research challenges, but …

With the widespread application of service-oriented architecture (SOA), a flood of similarly
functioning services have been deployed online. How to recommend services to users to …

In recent years, education institutions have offered a wide range of course selections with
overlaps. This presents significant challenges to students in selecting successful courses …

Owing to the enormous growth in information over the past few decades, the world has
become a global village. The recommendation system remains the most widely used type of …

Predicting students' performance is very important in matters related to higher education as
well as with regard to deep learning and its relationship to educational data. Prediction of …

In view of the poor recommendation performance of traditional resource collaborative
filtering recommendation algorithms, this article proposes a collaborative filtering …

Owing to the imbalance of observed data and user's preference, it is necessary and
meaningful to think over the multilevel characteristics of recommendation information (RI) …

Researchers and data scientists have developed different Recommender System Algorithms
such as Content-Based and Collaborative-Based in order to filter a large amount of …