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The mismatch between the number and quality of Information and Communication Technology (ICT) talents and industry needs in Indonesia creates significant challenges, especially for Informatics Engineering students who of...

This study presents the development of Scentify, a web and mobile-based perfume recommendation system employing the Content-Based Filtering (CBF) algorithm. The research aims to assist users in identifying perfumes align...

The rapid growth of e-commerce has led to product overload, which has resulted in personalized product discovery becoming a crucial problem for consumers. Classic recommender systems (RS), which rely heavily on content-b...

This research paper introduces UniEats, a recipe recommendation website designed to help university students better organize their meals and adopt healthier eating habits. The system aims to address common challenges stu...

The necessity for sophisticated recommender systems in the movie recommendation sphere has become particularly pronounced, generating a more personalized movie recommendation due to people nowadays who like to watch movi...

While traditional Project-based Learning (PjBL) enhances engagement, creativity, and conceptual understanding, emerging socioformative approaches are pedagogies that highlight the need for interdisciplinary, ethically gr...

Isu Smart Taourism (Wisata Pintar) memiliki topik populer dalam beberapa waktu terakhir, hasil ini dalam peningkatan jumlah prototipe pariwisata aplikasi desktop berbasis web dan berbasis mobile. Penelitian ini berfokus ...

Abstract Collaborative filtering and neural recommendation models have advanced substantially over the past decade, yet they frequently struggle to capture the fine-grained structure of user preferences and the rich, mul...

This study addresses the critical challenge of detecting duplicate final year project (FYP) titles in academic institutions, where minor variations like reordering, synonyms, and paraphrasing often obscure plagiarism. We...

"The steel industry faces increasing challenges in managing product diversity, maintaining competitiveness, and improving operational efficiency. Within this context, recommendation systems present a promising opportunit...

Recommender systems have been evaluated in many, often incomparable, ways. In this article, we review the key decisions in evaluating collaborative filtering recommender systems: the user tasks being evaluated, the types...

"En la era del turismo digital, las recomendaciones personalizadas se han vuelto esenciales para mejorar la experiencia del viajero. Esta tesis investiga el desarrollo de un sistema de recomendación turística utilizand...

This paper is based on an invited talk given at FLAIRS-38. It describes the evolution of harmful message detection and filtering, starting from individual message classification, to message prediction from conversations,...

This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main categories: content-based, coll...