Recommendation System-based Upper Confidence Bound for Online Advertising

Autor: Nguyen-Thanh, Nhan, Marinca, Dana, Khawam, Kinda, Rohde, David, Vasile, Flavian, Lohan, Elena Simona, Martin, Steven, Quadri, Dominique

In this paper, the method UCB-RS, which resorts to recommendation system (RS) for enhancing the upper-confidence bound algorithm UCB, is presented. The proposed method is used for dealing with non-stationary and large-state spaces multi-armed bandit

Externí odkaz: http://arxiv.org/abs/1909.04190

Forecasting Content Popularity: a Recommendation Method for Aggregating Predictors

Autor: Nguyen-Thanh, Nhan, Khawam, Kinda, Lohan, Elena Simona, Marinca, Dana, Martin, Steven, Quadri, Dominique, Boukhatem, Lila

Publikováno v: Knowledge and Information Systems (KAIS)
Knowledge and Information Systems (KAIS), Springer, In press

International audience; Currently, Video on Demand (VoD) is the heaviest data-driven service among various multimedia services. Therefore, predicting the popularity of mul-timedia contents, particularly video contents, in order to supply their proact

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a279403fae956cfae006461afe9f45ac
https://hal.archives-ouvertes.fr/hal-02284831/document

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Machine Learning and Popularity Prediction of a Video Content

Autor: Ben Hassine, Nesrine, Marinca, Dana, Pascale, Minet, Barth, Dominique

Publikováno v: The 4th International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN)
The 4th International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN), Nov 2015, Hammamet, Tunisia

International audience; — In Content Delivery Networks (CDNs), the knowledge of the popularity of video contents helps the manager to take efficient decisions about which video contents should be cached near the end users and also about the duplica

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a0b13c70e96666fd52b92987c82f3f6d
https://hal.inria.fr/hal-01244959/document

Caching strategies based on popularity prediction in content delivery networks.

Autor: Ben Hassine, Nesrine, Marinca, Dana, Minet, Pascale, Barth, Dominique

Publikováno v: 2016 IEEE 12th International Conference on Wireless & Mobile Computing, Networking & Communications (WiMob); 2016, p1-8, 8p