Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4960817 | Procedia Computer Science | 2017 | 6 Pages |
Abstract
Recommendation Systems of Applications (RSA) are based on various types of user information. Some of these systems analyze the influence of social networks information in the installation of apps. However, these approaches do not include all the relevant user information. The present paper proposes a technique for recommending mobile applications based on a social and context information. The approach is compared with two existing techniques showing improvements in the recommendation quality and high tolerance to a small number of data.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Dario Fernando Chamorro-Vela, Pablo Esteban Calvache-Lopez, Juan Carlos Corrales, Luis Antonio Rojas-Potosi, luis Javier Suares, Hugo Ordoñez, Armando Ordoñez,