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Imen Bizid
Researcher at University of La Rochelle
Publications - 9
Citations - 376
Imen Bizid is an academic researcher from University of La Rochelle. The author has contributed to research in topics: Microblogging & Event (computing). The author has an hindex of 6, co-authored 9 publications receiving 271 citations.
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Proceedings ArticleDOI
ICDAR2017 Robust Reading Challenge on Multi-Lingual Scene Text Detection and Script Identification - RRC-MLT
Nibal Nayef,Fei Yin,Imen Bizid,Hyun-Soo Choi,Yuan Feng,Dimosthenis Karatzas,Zhenbo Luo,Umapada Pal,Christophe Rigaud,Joseph Chazalon,Wafa Khlif,Muhammad Muzzamil Luqman,Jean-Christophe Burie,Cheng-Lin Liu,Jean-Marc Ogier +14 more
TL;DR: This paper presents the dataset, the tasks and the findings of this RRC-MLT challenge, which aims at assessing the ability of state-of-the-art methods to detect Multi-Lingual Text in scene images, such as in contents gathered from the Internet media and in modern cities where multiple cultures live and communicate together.
Proceedings ArticleDOI
Prominent Users Detection during Specific Events by Learning On- and Off-topic Features of User Activities
TL;DR: The achieved results show the effectiveness of the proposed model for both the classification and ranking of prominent users in such events, and also the importance of the adjustment of the on-topic features by the off-topic ones when describing users' activities.
Book ChapterDOI
MASIR: A Multi-agent System for Real-Time Information Retrieval from Microblogs During Unexpected Events
TL;DR: MASIR simplifies the real-time detection and tracking of the most prominent users by exploring both the old and fresh information shared during the event and outperforms the standard centrality measures by using a time-sensitive ranking model.
Journal ArticleDOI
Detecting prominent microblog users over crisis events phases
TL;DR: A phase-aware probabilistic model for predicting and ranking prominent microblog users over time according to their behavior using Mixture of Gaussians Hidden Markov Models (MoG-HMM) is proposed which takes into account both the user and the event specificities over time.
Book ChapterDOI
Integration of Heterogeneous Spatial Databases for Disaster Management
TL;DR: This paper aims to propose a framework for the integration of heterogeneous spatial databases using novel approaches, such as web services and ontologies, in order to be able to interrogate the content of the different databases conveniently.