Contextual aspects of typical viewing situations: a new perspective for recommending television and video content-Reference-Cited by-同舟云学术

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Contextual aspects of typical viewing situations: a new perspective for recommending television and video content

Published:2015-06-19 Issue:5-6 Volume:19 Page:761-779
ISSN:1617-4909
Container-title:Personal and Ubiquitous Computing
language:en
Short-container-title:Pers Ubiquit Comput

Author:

Vanattenhoven Jeroen,Geerts David

Publisher

Springer Science and Business Media LLC

Subject

Management Science and Operations Research,Computer Science Applications,Hardware and Architecture

Link

http://link.springer.com/content/pdf/10.1007/s00779-015-0861-0.pdf

Reference27 articles.

1. Herlocker JL, Konstan JA, Terveen LG, Riedl JT (2004) Evaluating collaborative filtering recommender systems. ACM Trans Inf Syst 22:5–53. doi: 10.1145/963770.963772

2. Adomavicius G, Tuzhilin A (2005) Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans Knowl Data Eng 17:734–749. doi: 10.1109/TKDE.2005.99

3. Dourish P (2004) What we talk about when we talk about context. Pers Ubiquit Comput 8:19–30. doi: 10.1007/s00779-003-0253-8

4. Churchill E (2013) Putting the person back into personalization. Interactions. 20:12–15

5. Masthoff J (2004) Group modeling: selecting a sequence of television items to suit a group of viewers. User Model User-Adapt Interact 14:37–85. doi: 10.1023/B:USER.0000010138.79319.fd

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1. Incorporating time-interval sequences in linear TV for next-item prediction;Expert Systems with Applications;2022-04

2. The Importance of Context When Recommending TV Content: Dataset and Algorithms;IEEE Transactions on Multimedia;2020-06

3. Browsing for Content Across Pay TV and On Demand Video Options;Proceedings of the 2019 ACM International Conference on Interactive Experiences for TV and Online Video;2019-06-04

4. A Dataset for Inferring Contextual Preferences of Users Watching TV;Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization;2018-07-03

5. A Data-driven Approach to Explore Television Viewing in the Household Environment;Proceedings of the 2018 ACM International Conference on Interactive Experiences for TV and Online Video;2018-06-25

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