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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...

As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest neighbor techniques for producing product recommendations, allowing the incorporation of additional informati...

This work presents a systematic literature review on the application of Machine Learning algorithms in the development of effective movie recommender systems. With the increasing popularity of movie recommender systems i...

"The selection of a suitable master’s program has become an increasingly complex task due to the growing diversity of offerings and the lack of standardized comparable information across institutions. This thesis propo...

Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a liveinteraction. These systems, especially the k-nearest neigh...

"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...