Design and implementation of a recommendation system

With the emergence of the Internet, recommender systems (SRs) arose because of their ability to handle massive amounts of information. SRs play a very important role in guiding users' decisions and making it easier for them. In addition, diet and its impact on well-being, metabolism and success in school, sport or work are becoming increasingly important. In this brief, we provide a systematic review of the SRs most closely related to healthcare. In addition, we offer "HealthyFood", a new food SR based on user knowledge, and incorporating machine learning (ML) techniques, which can be used to help people find relevant foods. In particular, we are implementing HealthyFood, the general idea of which we present in this work. Preliminary results indicate that integrating machine learning techniques into SRs will provide effective and accurate recommendations.

Autorentext

Houda El Bouhissi obtuvo su maestría y su doctorado en Informática en la Universidad de Sidi-Bel-Abbès (Argelia), en 2008 y 2015 respectivamente. En la actualidad, es profesora acreditada en la Universidad de Bejaia (Argelia). Sus intereses de investigación incluyen Big Data, análisis de sentimientos, aprendizaje y recomendación.