Implicit feedback techniques on recommender systems applied to electronic books

► The more time content is displayed by a user, the more he likes it. ► When a user accesses multiple times a category it is because he likes the contents. ► No strong relation between the display of items of a content and its ratings. The goal of this research is to define and capture a series of p...

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Veröffentlicht in:Computers in human behavior 2012-07, Vol.28 (4), p.1186-1193
Hauptverfasser: Núñez-Valdéz, Edward Rolando, Cueva Lovelle, Juan Manuel, Sanjuán Martínez, Oscar, García-Díaz, Vicente, Ordoñez de Pablos, Patricia, Montenegro Marín, Carlos Enrique
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container_end_page 1193
container_issue 4
container_start_page 1186
container_title Computers in human behavior
container_volume 28
creator Núñez-Valdéz, Edward Rolando
Cueva Lovelle, Juan Manuel
Sanjuán Martínez, Oscar
García-Díaz, Vicente
Ordoñez de Pablos, Patricia
Montenegro Marín, Carlos Enrique
description ► The more time content is displayed by a user, the more he likes it. ► When a user accesses multiple times a category it is because he likes the contents. ► No strong relation between the display of items of a content and its ratings. The goal of this research is to define and capture a series of parameters that allowed us to perform a comparative analysis and find correlations between explicit and implicit feedback on recommender systems. Most of these systems require explicit actions from the users, such as rating, and commenting. In the context of electronic books this interaction may alter the patterns of reading and understanding of the users, as they are asked to stop reading and rate the content. By simulating the behavior of an electronic book reader we have improved the feedback process, by implicitly capturing, measuring, and classifying the information needed to discover user interests. In these times of information overload, we can now develop recommender systems that are mostly based on the user’s behavior, by relying on the obtained results.
doi_str_mv 10.1016/j.chb.2012.02.001
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source Elsevier ScienceDirect Journals
subjects Applied psychology
Biological and medical sciences
Classification
Computer simulation
Explicit feedback
Feedback
Fundamental and applied biological sciences. Psychology
Human behavior
Implicit feedback
Mathematical models
Miscellaneous
Plugs
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Readers
Recommender system
title Implicit feedback techniques on recommender systems applied to electronic books
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