Recommendation of Mobile Applications based on social and contextual user information | Zendy

Dario Fernando Chamorro-Vela | Zendy; Pablo Esteban Calvache-Lopez | Zendy; Juan Carlos Corrales | Zendy; Luis Antonio Rojas-Potosí | Zendy; luis Javier Suares | Zendy; Hugo Ordóñez | Zendy; Armando Ordóñez | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Recommendation of Mobile Applications based on social and contextual user information

Author(s) -

Dario Fernando Chamorro-Vela,

Pablo Esteban Calvache-Lopez,

Juan Carlos Corrales,

Luis Antonio Rojas-Potosí,

luis Javier Suares,

Hugo Ordóñez,

Armando Ordóñez

Publication year - 2017

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2017.06.090

Subject(s) - computer science , recommender system , context (archaeology) , information quality , quality (philosophy) , world wide web , mobile device , information system , electrical engineering , biology , engineering , paleontology , philosophy , epistemology

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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research