Next Article in Journal
Influence of Aggregate Gradation on the Engineering Properties of Lightweight Aggregate Concrete
Previous Article in Journal
Grinding Kinetics Adjustment of Copper Ore Grinding in an Innovative Electromagnetic Mill
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Appl. Sci. 2018, 8(8), 1323; https://doi.org/10.3390/app8081323

A Television Recommender System Learning a User’s Time-Aware Watching Patterns Using Quadratic Programming

1
Department of Electrical and Computer Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do 16419, Korea
2
Samsung Electronics, 1-1 Samsungjeonja-ro, Hwaseong-si, Gyeonggi-do 18448, Korea
*
Author to whom correspondence should be addressed.
Received: 10 July 2018 / Revised: 24 July 2018 / Accepted: 5 August 2018 / Published: 8 August 2018
(This article belongs to the Section Computer Science and Electrical Engineering)
Full-Text   |   PDF [1906 KB, uploaded 8 August 2018]   |  

Abstract

In this paper, a novel television (TV) program recommendation method is proposed by merging multiple preferences. We use channels and genres of programs, which is available information in standalone TVs, as features for the recommendation. The proposed method performs multi-time contextual profiling and constructs multiple-time contextual preference matrices of channels and genres. Since multiple preference models are constructed with different time contexts, there can be conflicts among them. In order to effectively merge the preferences with the minimum number of conflicts, we develop a quadratic programming model. The optimization problem is formulated with a minimum number of constraints so that the optimization process is scalable and fast even in a standalone TV with low computational power. Experiments with a real-world dataset prove that the proposed method is more efficient and accurate than other TV recommendation methods. Our method improves recommendation performance by 5–50% compared to the baselines. View Full-Text
Keywords: context awareness; recommender systems; time-aware recommendation; time context; TV program recommendation; quadratic programming context awareness; recommender systems; time-aware recommendation; time context; TV program recommendation; quadratic programming
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Kim, N.-R.; Oh, S.; Lee, J.-H. A Television Recommender System Learning a User’s Time-Aware Watching Patterns Using Quadratic Programming. Appl. Sci. 2018, 8, 1323.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top