Big Data Recommender System - Couverture souple

Atanassov, Atanas; Al-Barznji, Kamal

Couverture souple

ISBN 10 : 6139883644 ISBN 13 : 9786139883646

Editeur : LAP LAMBERT Academic Publishing, 2018

Synopsis

Recommendation Systems provide the facility to understand a person’s taste and find new. As one of the most successful approaches to build recommender systems, collaborative filtering (CF) uses the known preferences of a group of users to make recommendations or predictions of the unknown preferences for other users. In this research, we first introduce recommendation systems and CF, then we have proposed a system for generating recommendations on a Big amount of Data by memory based filtering techniques (User-based and Item-based). These techniques require no knowledge of properties of items and characteristics, they only use the information in the rating matrix. We have implemented these recommendation algorithms on Hadoop platform using Apache Mahout, a Machine Learning tool, to provide a scalable system for processing huge data sets efficiently. Finally, we compared and discussed the results of the both techniques to determine their quality of generating recommendations.

Détails de l'édition

• Éditeur: LAP LAMBERT Academic Publishing
• Date d'édition: 2018
• Langue: anglais
• ISBN 10: 6139883644
• ISBN 13: 9786139883646
• Reliure: Broché
• Nombre de pages: 60
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible