Social Recommender System

García, Cristian González; Meana-Llorián, Daniel; García‐Díaz, Vicente; Núñez‐Valdéz, Edward Rolando

doi:10.1145/3092090.3092121

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2018

2023

Publication Types

Select...

Article1

Other1

Relationship

Self Cite1

Independent1

Authors

Journals

Cited by 2 publications

(1 citation statement)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, social networks are a source of information that can help improve users' experience through the use of recommender systems. In [13] a first approach is presented for the development of a platform that allows the analysis of users' comments on social networks with the objective of making recommendations that improve users' satisfaction with the network.…”

Section: Introductionmentioning

confidence: 99%

A recommender system based on implicit feedback for selective dissemination of ebooks

Núñez‐Valdéz

Quintana

Crespo

et al. 2018

Information Sciences

Self Cite

View full text Add to dashboard Cite

In this study, we describe a recommendation system for electronic books. The approach is based on implicit feedback derived from user's interaction with electronic content. User's behavior is tracked through several indicators that are subsequently used to feed the recommendation engine. This component then provides an explicit rating for the material interacted with. The role of this engine could be modeled as a regression task where content is rated according to the mentioned indicators. In this context, we benchmark twelve popular machine learning algorithms to perform this final function and evaluate the quality of the output provided by the system.

show abstract

Section: Introductionmentioning

confidence: 99%