A Nondisturbing Service to Automatically Customize Notification Sending Using Implicit-Feedback
Joint Authors
López Hernández, Fernando
Pérez, Elena Verdú
Rainer Granados, J. Javier
González Crespo, Rubén
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-03
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
This paper addresses the problem of automatically customizing the sending of notifications in a nondisturbing way, that is, by using only implicit-feedback.
Then, we build a hybrid filter that combines text mining content filtering and collaborative filtering to predict the notifications that are most interesting for each user.
The content-based filter clusters notifications to find content with topics for which the user has shown interest.
The collaborative filter increases diversity by discovering new topics of interest for the user, because these are of interest to other users with similar concerns.
The paper reports the result of measuring the performance of this recommender and includes a validation of the topics-based approach used for content selection.
Finally, we demonstrate how the recommender uses implicit-feedback to personalize the content to be delivered to each user.
American Psychological Association (APA)
López Hernández, Fernando& Pérez, Elena Verdú& Rainer Granados, J. Javier& González Crespo, Rubén. 2019. A Nondisturbing Service to Automatically Customize Notification Sending Using Implicit-Feedback. Scientific Programming،Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1210714
Modern Language Association (MLA)
López Hernández, Fernando…[et al.]. A Nondisturbing Service to Automatically Customize Notification Sending Using Implicit-Feedback. Scientific Programming No. 2019 (2019), pp.1-17.
https://search.emarefa.net/detail/BIM-1210714
American Medical Association (AMA)
López Hernández, Fernando& Pérez, Elena Verdú& Rainer Granados, J. Javier& González Crespo, Rubén. A Nondisturbing Service to Automatically Customize Notification Sending Using Implicit-Feedback. Scientific Programming. 2019. Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1210714
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1210714