Recommending Ads from Trustworthy Relationships in Pervasive Environments
Joint Authors
Martinez-Pabon, Francisco
Ramirez-Gonzalez, Gustavo
Muñoz-Organero, Mario
Ospina-Quintero, Juan Camilo
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-07-31
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Telecommunications Engineering
Abstract EN
The use of pervasive computing technologies for advertising purposes is an interesting emergent field for large, medium, and small companies.
Although recommender systems have been a traditional solution to decrease users’ cognitive effort to find good and personalized items, the classic collaborative filtering needs to include contextual information to be more effective.
The inclusion of users’ social context information in the recommendation algorithm, specifically trust in other users, may be a mechanism for obtaining ads’ influence from other users in their closest social circle.
However, there is no consensus about the variables to use during the trust inference process, and its integration into a classic collaborative filtering recommender system deserves a deeper research.
On the other hand, the pervasive advertising domain demands a recommender system evaluation from a novelty/precision perspective.
The improvement of the precision/novelty balance is not only a matter related to the recommendation algorithm itself but also a better recommendations’ display strategy.
In this paper, we propose a novel approach for a collaborative filtering recommender system based on trust, which was tested throughout a digital signage prototype using a multiscreen scheme for recommendations delivery to evaluate our proposal using a novelty/precision approach.
American Psychological Association (APA)
Martinez-Pabon, Francisco& Ospina-Quintero, Juan Camilo& Ramirez-Gonzalez, Gustavo& Muñoz-Organero, Mario. 2016. Recommending Ads from Trustworthy Relationships in Pervasive Environments. Mobile Information Systems،Vol. 2016, no. 2016, pp.1-18.
https://search.emarefa.net/detail/BIM-1111633
Modern Language Association (MLA)
Martinez-Pabon, Francisco…[et al.]. Recommending Ads from Trustworthy Relationships in Pervasive Environments. Mobile Information Systems No. 2016 (2016), pp.1-18.
https://search.emarefa.net/detail/BIM-1111633
American Medical Association (AMA)
Martinez-Pabon, Francisco& Ospina-Quintero, Juan Camilo& Ramirez-Gonzalez, Gustavo& Muñoz-Organero, Mario. Recommending Ads from Trustworthy Relationships in Pervasive Environments. Mobile Information Systems. 2016. Vol. 2016, no. 2016, pp.1-18.
https://search.emarefa.net/detail/BIM-1111633
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1111633