C
Chedy Raïssi
Researcher at French Institute for Research in Computer Science and Automation
Publications - 65
Citations - 1272
Chedy Raïssi is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Set (abstract data type) & Domain knowledge. The author has an hindex of 19, co-authored 65 publications receiving 1106 citations. Previous affiliations of Chedy Raïssi include University of Montpellier & University of Lorraine.
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Proceedings ArticleDOI
Watch me playing, i am a professional: a first study on video game live streaming
TL;DR: A first characterization of a new Web community is proposed, and it is shown that the number of viewers of a streaming session evolves in a predictable way, that audience peaks of a game are explainable and that a Condorcet method can be used to sensibly rank the streamers by popularity.
Journal ArticleDOI
ρ-uncertainty: inference-proof transaction anonymization
TL;DR: The problem of achieving ρ-uncertainty with low information loss is solved non-trivially by a technique that combines generalization and suppression, which achieves favorable results compared to a baseline perturbation-based scheme.
Proceedings ArticleDOI
Mining Dominant Patterns in the Sky
TL;DR: This work establishes theoretical relationships between pattern condensed representations and skyline pattern mining and shows that it is possible to compute automatically a subset of measures involved in the user query which allows the patterns to be condensed and thus facilitates the computation of the skyline patterns.
Journal ArticleDOI
Scientific Domain Knowledge Improves Exoplanet Transit Classification with Deep Learning
Megan Ansdell,Yani Ioannou,Hugh P. Osborn,Michele Sasdelli,Jeffrey C. Smith,Jeffrey C. Smith,Douglas A. Caldwell,Douglas A. Caldwell,Jon M. Jenkins,Chedy Raïssi,Daniel Angerhausen +10 more
TL;DR: This work illustrates the importance of including expert domain knowledge in even state-of-the-art deep learning models when applying them to scientific research problems that seek to identify weak signals in noisy data.
Proceedings ArticleDOI
Modeling and Analyzing the Video Game Live-Streaming Community
Gustavo Nascimento,Manoel Horta Ribeiro,Loïc Cerf,Natalia Cesario,Mehdi Kaytoue,Chedy Raïssi,Thiago Vasconcelos,Wagner Meira +7 more
TL;DR: A model to characterize how streamers and spectators behave, based on their possible actions in Twitch, is proposed and, using it, a case study is performed on the Star craft II streamer and spectators.