Soumyadeep PATY; Arindam BISWAS; Sonia Djebali; Guillaume Guérard; Supreeti KAMILYA
IoT-Enabled Methane Monitoring and LSTM-Based Forecasting System for Enhanced Safety in Underground Coal Mining Article de journal
Dans: ACM Transactions on Internet of Things, vol. 6, no. 1, 2025.
@article{paty_3212,
title = {IoT-Enabled Methane Monitoring and LSTM-Based Forecasting System for Enhanced Safety in Underground Coal Mining},
author = {Soumyadeep PATY and Arindam BISWAS and Sonia Djebali and Guillaume Guérard and Supreeti KAMILYA},
url = {https://dl.acm.org/doi/pdf/10.1145/3703460},
year = {2025},
date = {2025-01-01},
journal = {ACM Transactions on Internet of Things},
volume = {6},
number = {1},
abstract = {Ensuring safety in the mining industry is a critical concern for a nation's industrial advancement. Industry 4.0, characterized by the integration of advanced technologies, is at the forefront of efforts to enhance mining practices. Coal seams contain a range of
hydrocarbon gases, predominantly methane, which is released in significant quantities during mining operations. Effectively
mitigating methane emissions is imperative. The inclusion of methane forecasting allows for the early identification of potential methane emissions, hence results in significance enhancement in mine safety. The research work is focused on real-time remote monitoring and cloud-based forecasting of methane levels in underground coal mines. An Industrial Internet of Things (IIoT) device is developed for data acquisition in underground coal mines, capturing essential parameters such as methane concentration,
temperature, and humidity. The collected data are utilized to train LSTM based multivariate forecasting model. The trained model is
subsequently deployed in the cloud. The experiment is performed in a mine of Eastern Coalfields Limited, India. After the deployment
of the proposed model, the developed IIoT device transmits real-time data, obtained from the mine, to the cloud. Based on the real
time data, our model conducts methane forecasting and communicates results back to the IIoT device. The device issues immediate
alerts when methane levels surpass predefined thresholds. This ensures enhanced safety in mining operations by providing warnings
for both current and forecasted methane concentrations. The forecasted methane concentrations, along with real-time data, are
accessible through mobile applications and a web-based dashboard. The accuracy of the proposed model is measured by mean
absolute error, mean absolute percentage error and root mean square error, which demonstrate values of 156.95 ppm, 4.23% and
191.53 ppm respectively. A comparative study is performed where our model is evaluated against the multivariate Multilayer
Perceptron (MLP), Vector autoregression (VAR) and Auto-Regressive Integrated Moving Average (ARIMA) models. The comparative
study demonstrates that our developed model outperforms the others, showing superior results.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Yuehgoh Foutse; Sonia Djebali; Nicolas Travers
Leveraging recommendations using a multiplex graph database Article de journal
Dans: International Journal of Web Information Systems, vol. 20, no. 5, p. 537-582, 2024.
@article{foutse_3196,
title = {Leveraging recommendations using a multiplex graph database},
author = {Yuehgoh Foutse and Sonia Djebali and Nicolas Travers},
url = {https://www.emerald.com/insight/content/doi/10.1108/IJWIS-05-2024-0137/full/html},
year = {2024},
date = {2024-10-01},
journal = {International Journal of Web Information Systems},
volume = {20},
number = {5},
pages = {537-582},
abstract = {Purpose
By applying targeted graph algorithms, the method used by the authors enables effective prediction of user interactions and thus fulfils the complex requirements of modern recommender systems. This study sets a new benchmark for multidimensional recommendation strategies and offers a path towards more advanced and user-centric models.
Design/methodology/approach
To improve multidimensional data recommendation systems, multiplex graph structures are useful to capture various types of user interactions. This paper presents a novel framework that uses a graph database to compute and manipulate multiplex graphs. The approach enables flexible dimension management and increases expressive power through a specialised algebra designed for multiplex graph manipulation.
Findings
The authors compare the multiplex graph approach with traditional matrix methods, in particular random walk with restart, and show that the method not only provides deeper insights into user preferences by integrating scores from different layers of the multiplex graph, but also outperforming matrix-based approaches in most configurations. The results highlight the potential of multiplex graphs for developing sophisticated and customised recommender systems that significantly improve both performance and explainability.
Originality/value
The study provides a formal specification of a multiplex graph construction based on interaction and content-based information; and the study also developed an algebra dedicated to multiplex graphs, enabling robust and precise graph manipulations necessary for effective recommendation queries. The authors implement these algebraic operations within the Neo4j graph database system with a thorough analysis and experimentation with three different data sets, benchmarked against traditional matrix-based methods.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Shrabani Sutradhar; Sunil Karforma; Rajesh Bose; Sandip Roy; Sonia Djebali; Debnath Bhattacharyya
Enhancing identity and access management using Hyperledger Fabric and OAuth 2.0: A block-chain-based approach for security and scalability for healthcare industry Article de journal
Dans: Internet of Things and Cyber-Physical Systems, vol. 4, p. 49-67, 2024.
@article{sutradhar_3061,
title = {Enhancing identity and access management using Hyperledger Fabric and OAuth 2.0: A block-chain-based approach for security and scalability for healthcare industry},
author = {Shrabani Sutradhar and Sunil Karforma and Rajesh Bose and Sandip Roy and Sonia Djebali and Debnath Bhattacharyya},
url = {https://doi.org/10.1016/j.iotcps.2023.07.004},
year = {2024},
date = {2024-07-01},
journal = {Internet of Things and Cyber-Physical Systems},
volume = {4},
pages = {49-67},
abstract = {Block-chain-based Identity and access management framework is a promising solution to privacy and security issues raised during the exchange of patient data in the healthcare industry. This technology ensures the confidentiality and integrity of sensitive information by providing a decentralized and immutable ledger. In our research, we propose an identity and access management system that employs Hyper-ledger Fabric and OAuth 2.0 for improved security and scalability. This combination allows for transparency and immutability of user transactions and minimizes the risk of fraud and unauthorized access. Additionally, Hyper-ledger Fabric's privacy, security, and scalability features enable granular access control to sensitive information, while OAuth 2.0 authorizes only trusted third-party applications to access specific data on the Fabric network. The proposed approach can handle large volumes of data and support multiple applications, thus providing a secure and scalable solution for managing access to the Fabric network. Moreover, our solution employs Role-based access control based on the patient's role, ensuring privacy and confidentiality. Our statistical analysis demonstrates that the proposed approach can efficiently and securely manage patient identity and access, potentially transforming the healthcare industry by enhancing data interoperability, reducing fraud and errors, and improving patient privacy and security. Furthermore, our solution can facilitate compliance with regulatory requirements such as HIPAA and GDPR.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Sonia Djebali; Guillaume Guérard; Ihab Taleb
Survey and insights on digital twins design and smart grid's applications Article de journal
Dans: Future Generation Computer Systems-The International Journal Of Escience, vol. 153, p. 234-248, 2024.
@article{djebali_2538,
title = {Survey and insights on digital twins design and smart grid's applications},
author = {Sonia Djebali and Guillaume Guérard and Ihab Taleb},
url = {https://www.sciencedirect.com/science/article/pii/S0167739X23004466},
year = {2024},
date = {2024-04-01},
journal = {Future Generation Computer Systems-The International Journal Of Escience},
volume = {153},
pages = {234-248},
abstract = {Digital twins are a promising technology for simulating complex systems, especially in the smart grid domain. This paper offers a comprehensive literature review on digital twins, focusing on data gathering, data management, and human-in-the-loop control design aspects. Emphasizing the integration of AI and machine learning in big data, it enhances analytics and decision-making capabilities. We introduce a collaborative framework involving multiple stakeholders to maximize the potential of digital twins. The paper examines digital twin applications in smart grids, covering areas like asset management, predictive maintenance, energy optimization, and demand response. By synthesizing research and implementation findings, we identify trends, challenges, and opportunities in the field.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Guillaume Guérard; Quentin Gabot; Sonia Djebali
Tourism profile measure for?data?driven tourism segmentation Article de journal
Dans: International Journal Of Machine Learning And Cybernetics, 2024.
@article{guerard_2939,
title = {Tourism profile measure for?data?driven tourism segmentation},
author = {Guillaume Guérard and Quentin Gabot and Sonia Djebali},
url = {https://link.springer.com/article/10.1007/s13042-024-02145-z},
year = {2024},
date = {2024-04-01},
journal = {International Journal Of Machine Learning And Cybernetics},
abstract = {The digital revolution has brought about profound changes in research within the tourism segmentation field. The ease of grasping tourists' behaviors is facilitated by the digital traces left on social networks. Existing studies focusing on tourists' digital traces typically apply clustering algorithms to the tourism context. This paper introduces a novel measure, named tourism profile measure for determining tourism segmentation, also known as tourism profiling. The approach involves establishing a new clustering algorithm that centers on stays conducted by tourists, utilizing both the context and content of the trips. The proposed measure is then simulated and experimentally evaluated using a real dataset across various periods and diverse nationalities, particularly in the context of the French capital, Paris.},
keywords = {},
pubstate = {online},
tppubtype = {article}
}
Yuehgoh Foutse; Sonia Djebali; Nicolas Travers
A Multiplex Graph for Recommending Multidimensional Documents Conférence
40ème conférence sur la gestion des données, Orléans, France, 2024.
@conference{foutse_3157,
title = {A Multiplex Graph for Recommending Multidimensional Documents},
author = {Yuehgoh Foutse and Sonia Djebali and Nicolas Travers},
url = {https://bda2024.sciencesconf.org/resource/page/id/7},
year = {2024},
date = {2024-10-01},
booktitle = {40ème conférence sur la gestion des données},
address = {Orléans, France},
abstract = {Network Science has become a flourishing interest in the last
decades with the Big Data explosion. To improve multidimensional data
Recommendation Systems, multiplex graph structures are useful to cap-
ture various types of user interactions. We propose a graph database
approach to compute multiplex graphs which helps both manipulating
dimensions in a flexible way and enhancing expressiveness with algebra
to express manipulations on the multiplex graph. Applied operations
rely on graph algorithms to predict user interactions. We compare our
approach with the traditional matrix approach with Random Walk with
Restart. The study shows that combination of scores from layers of mul-
tiplex graphs provide important insights into user preferences, with most
configurations outperforming traditional matrix methods. This approach
provides a comprehensive analysis of multidimensional recommendation
strategies in multiplex graphs, which provides capabilities of managing
different dimensions for queries, paving the way for more sophisticated
and customized recommendation systems and its explicability.},
note = {du 21 au 24/10/2024},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Yuehgoh Foutse; Sonia Djebali; Nicolas Travers
How to recommend Multidimensional Documents with a Multiplex Graph? Conférence
Deep Learning Indaba, Dakar, Sénégal, 2024.
@conference{foutse_3140,
title = {How to recommend Multidimensional Documents with a Multiplex Graph?},
author = {Yuehgoh Foutse and Sonia Djebali and Nicolas Travers},
url = {https://deeplearningindaba.com/2024/posters/},
year = {2024},
date = {2024-09-01},
booktitle = {Deep Learning Indaba},
address = {Dakar, Sénégal},
note = {du 01/09/2024 au 07/09/2024},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Hugo Alatrista Salas; Gaël Chareyron; Sonia Djebali; Imen Ouled Dlala; Nicolas Travers
SuPreME: Sequential Pattern Mining for Understanding Multiscale Seasonal Tourist Behavior Conférence
GdR MADICS, Blois, France, 2024.
@conference{alatrista_salas_3045,
title = {SuPreME: Sequential Pattern Mining for Understanding Multiscale Seasonal Tourist Behavior},
author = {Hugo Alatrista Salas and Gaël Chareyron and Sonia Djebali and Imen Ouled Dlala and Nicolas Travers},
editor = {CNRS},
url = {https://www.madics.fr/event/symposium-madics-6/#ListePosters},
year = {2024},
date = {2024-05-01},
booktitle = {GdR MADICS},
address = {Blois, France},
note = {29-30/05/2024},
keywords = {},
pubstate = {online},
tppubtype = {conference}
}
Guillaume Guérard; Sofiane Ben Amor; Maxence Choufa; Sonia Djebali; Clement Cornet; Loup-Noé Levy; Hai Tran
Pretopology-based Clustering for Mixed Data Conférence
ROADEF 2023, Rennes , France, 2023.
@conference{guerard_2244,
title = {Pretopology-based Clustering for Mixed Data},
author = {Guillaume Guérard and Sofiane Ben Amor and Maxence Choufa and Sonia Djebali and Clement Cornet and Loup-Noé Levy and Hai Tran},
url = {https://roadef2023.sciencesconf.org/436878/document},
year = {2023},
date = {2023-02-01},
booktitle = {ROADEF 2023},
address = {Rennes , France},
abstract = {The energy performance of buildings represents a major issue of the 21st century. Many
solutions have been discussed to improve buildings' energy performance [1, 4], but the actions
to take differ from one building to another. In other words, current solutions are built on
a case-by-case basis and cannot be extrapolated easily. Indeed, it is difficult to find generic
solutions due to their complexity and heterogeneity.
By placing buildings in groups and subgroups, one can define relevant energy optimization
recommendations without auditing each building individually. Because initial labels are not
always defined, clustering is relevant in our case. Since we seek for intrinsic similarities between
groups and subgroups, hierarchical clustering is needed. Buildings are described with mixed
data. They include numerical data such as surface or number of floors, and categorical data like
types of heating or insulation materials. Few clustering algorithms exist for mixed data, and
even fewer are hierarchical. In this article, we present a method for the hierarchical clustering
of mixed data based on pretopology.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Yuehgoh Foutse; Sonia Djebali; Nicolas Travers
A recommendation system for technology intelligence based on multiplex networks Conférence
17th Women in Machine Learning Workshop @ NeurIPS, New Orleans, USA, 2022.
@conference{foutse_2060,
title = {A recommendation system for technology intelligence based on multiplex networks},
author = {Yuehgoh Foutse and Sonia Djebali and Nicolas Travers},
url = {https://sites.google.com/view/wiml2022},
year = {2022},
date = {2022-11-01},
booktitle = {17th Women in Machine Learning Workshop @ NeurIPS},
address = {New Orleans, USA},
abstract = {A recommendation system for technology intelligence based on multiplex networks},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Yuehgoh Foutse; Sonia Djebali; Nicolas Travers
A Technology Intelligence Recommendation System based on Multiplex Networks Conférence
MaDICS 2022, CNRS Lyon, France, 2022.
@conference{foutse_1833,
title = {A Technology Intelligence Recommendation System based on Multiplex Networks},
author = {Yuehgoh Foutse and Sonia Djebali and Nicolas Travers},
url = {https://www.madics.fr/event/symposium-madics-4/},
year = {2022},
date = {2022-07-01},
booktitle = {MaDICS 2022},
pages = {2},
address = {Lyon, France},
organization = {CNRS},
abstract = {Mon travail de recherche se focalise sur les systèmes de recommandation pour la veille technologique chez COEXEL, une société fondée par Vincent Boisard, acteur majeur de ce domaine grâce à son outil de gestion électronique de l'information basée sur le web, appelée Mytwip®. Ces données ciblées correspondent à des évolutions technologiques visibles sur le Web pour lesquelles un expert du domaine souhaite rester informé de la concurrence ou des usages.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Quentin Gabot; Guillaume Guérard; Sonia Djebali
Tourists profiling by interest analysis Conférence
Groupe de Recherche : Masses de Données, Informations et Connaissances en Sciences (MADICS), CNRS Lyon, France, 2022.
@conference{gabot_2245,
title = {Tourists profiling by interest analysis},
author = {Quentin Gabot and Guillaume Guérard and Sonia Djebali},
url = {https://www.madics.fr/},
year = {2022},
date = {2022-07-01},
booktitle = {Groupe de Recherche : Masses de Données, Informations et Connaissances en Sciences (MADICS)},
address = {Lyon, France},
organization = {CNRS},
abstract = {With the recent digital revolution, analyzing of tourists' behaviorsand research fields associated with it have changed profoundly.It is now easier to examine behaviors of tourists using digital traces they leave during their travels. The studies conducted on diverse aspects of tourism focus on quantitative aspects of digital traces to reach its conclusions.In this paper, we suggest a study focused on both qualitative andquantitative aspect of digital traces to understand the dynamics governing tourist behavior, especially those concerning attractions networks.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Sonia Djebali; Nicolas Travers; Gaël Chareyron
Indicateurs de Mesure pour la Mobilité Touristique Conférence
40ème Congrès INFORSID 2022, Dijon, France, 2022.
@conference{djebali_1832,
title = {Indicateurs de Mesure pour la Mobilité Touristique},
author = {Sonia Djebali and Nicolas Travers and Gaël Chareyron},
url = {https://inforsid2022.sciencesconf.org/},
year = {2022},
date = {2022-05-01},
booktitle = {40ème Congrès INFORSID 2022},
pages = {4},
address = {Dijon, France},
abstract = {Les traces numériques laissées par les utilisateurs sur les réseaux sociaux sont deve- nues un moyen populaire d'analyse du comportement des touristes dont l'analyse a un impact dans le marketing touristique pour construire des outils d'aide à la décision dans le tourisme. Nous proposons des mesures pour capturer la mobilité et la propagation touristique sur diffé- rentes zones qui s'appuie sur le réseau TripAdvisor et la base de données graphes Neo4j.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Lillia Ben Baccar; Sonia Djebali; Guillaume Guérard
Prédiction de Circuit Touristique par Data Mining Séquentielle Conférence
Premier Symposium GDR MaDICS, Rennes, France, 2019.
@conference{ben_baccar_889,
title = {Prédiction de Circuit Touristique par Data Mining Séquentielle},
author = {Lillia Ben Baccar and Sonia Djebali and Guillaume Guérard},
url = {http://www.madics.fr/event/titre1551974198-3309/#posters},
year = {2019},
date = {2019-06-01},
booktitle = {Premier Symposium GDR MaDICS},
address = {Rennes, France},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Ravi Kiran Bagadi; Sonia Djebali
Groundwater Quality Monitoring Using Machine Learning and Image Processing Techniques Book Section
Dans: Arindam Biswas Supreeti Kamilya, Sheng-Lung Peng (Ed.): Water Informatics Challenges and Solutions Using State of Art Technologies, vol. 18, p. 83-105, Springer Singapore, Singapore, 2024, ISBN: 978-981-97-1518-3.
@incollection{kiran_bagadi_3204,
title = {Groundwater Quality Monitoring Using Machine Learning and Image Processing Techniques},
author = {Ravi Kiran Bagadi and Sonia Djebali},
editor = {Supreeti Kamilya, Arindam Biswas, Sheng-Lung Peng},
url = {https://link.springer.com/chapter/10.1007/978-981-97-1518-3_7},
issn = {978-981-97-1518-3},
year = {2024},
date = {2024-06-01},
booktitle = {Water Informatics Challenges and Solutions Using State of Art Technologies},
volume = {18},
pages = {83-105},
publisher = {Springer Singapore},
address = {Singapore},
abstract = {Groundwater quality monitoring is critical for sustainable water resource management. Traditional methods of groundwater quality monitoring can be time-consuming, expensive and labour-intensive. In recent years, there has been an increase in interest in employing machine learning and image processing techniques to monitor groundwater quality. In this study, we reviewed different methods for monitoring groundwater quality utilising machine learning and image processing techniques. Our method is divided into four stages: data collection, pre-processing, feature extraction and classification. We use image enhancement techniques in the pre-processing stage to increase the quality of the acquired photographs.},
keywords = {},
pubstate = {online},
tppubtype = {incollection}
}
Yuehgoh Foutse; Sonia Djebali; Nicolas Travers
How to Recommend Multidimensional Data with a Multiplex Graph? Proceedings Article
Dans: Asian Conference on Intelligent Information and Database Systems, p. 332-344, Springer, Ras Al Khaimah, UAE, 2024, ISBN: 978-981-97-4984-3.
@inproceedings{foutse_2898,
title = {How to Recommend Multidimensional Data with a Multiplex Graph?},
author = {Yuehgoh Foutse and Sonia Djebali and Nicolas Travers},
url = {https://aciids.pwr.edu.pl/2024/index.php#about},
issn = {978-981-97-4984-3},
year = {2024},
date = {2024-07-01},
booktitle = {Asian Conference on Intelligent Information and Database Systems},
volume = {LNAI 14796},
pages = {332-344},
publisher = {Springer},
address = {Ras Al Khaimah, UAE},
abstract = {Network Science has become a flourishing interest in the last decades with the Big Data explosion. To improve multidimensional data Recommendation Systems, multiplex graph structures are useful to capture various types of user interactions. We propose a graph database approach to compute multiplex graphs which helps both manipulating dimensions in a flexible way and enhancing expressiveness with algebra to express manipulations on the multiplex graph. Applied operations rely on graph algorithms to predict user interactions. We compare our approach with the traditional matrix approach with Random Walk with Restart. The study shows that combination of scores from layers of multiplex graphs provide important insights into user preferences, with most configurations outperforming traditional matrix methods.
This approach provides a comprehensive analysis of multidimensional recommendation strategies in multiplex graphs, which provides capabilities of managing different dimensions for queries, paving the way for more sophisticated and customized recommendation systems and its explicability.},
note = {16th Asian Conference on Intelligent Information and Database Systems
15-18 April 2024, Ras Al Khaimah, UAE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Guillaume Guérard; Sonia Djebali
Omics Challenges in Health and Biology Proceedings Article
Dans: ROADEF 2024, Amiens, France, 2024.
@inproceedings{guerard_3074,
title = {Omics Challenges in Health and Biology},
author = {Guillaume Guérard and Sonia Djebali},
url = {https://roadef2024.sciencesconf.org/},
year = {2024},
date = {2024-03-01},
booktitle = {ROADEF 2024},
address = {Amiens, France},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Sonia Djebali; Guillaume Guérard; Loup-Noé Levy
Clustering Mixed Data Comprising Time Series Proceedings Article
Dans: SOICT '23: Proceedings of the 12th International Symposium on Information and Communication Technology, p. 110-117, Ho Chi Minh, Vietnam, 2023, ISBN: 9798400708916.
@inproceedings{djebali_3062,
title = {Clustering Mixed Data Comprising Time Series},
author = {Sonia Djebali and Guillaume Guérard and Loup-Noé Levy},
url = {https://doi.org/10.1145/3628797.3628968},
issn = {9798400708916},
year = {2023},
date = {2023-12-01},
booktitle = {SOICT '23: Proceedings of the 12th International Symposium on Information and Communication Technology},
pages = {110-117},
address = {Ho Chi Minh, Vietnam},
abstract = {The health and medicine sector is currently experiencing significant transformations, such as the integration of artificial intelligence in the decision-making process. In this complex system, there is a continuous data flow consisting of quantitative, qualitative, ordinal types, and time series. Hierarchical clustering is a useful tool to handle this complexity. However, clustering mixed data containing time series without distorting the inherent nature of the data poses a challenge. Although there are existing clustering techniques for mixed data or time series, the literature does not address the clustering of mixed data and time series. This paper presents several methodologies for such data clustering, including a novel algorithm based on pretopology. This hierarchical algorithm allows for customizable logical clustering, enabling health experts to better interpret and utilize the results for classification and recommendation by analyzing the hierarchy of clusters.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Sonia Djebali; Quentin Gabot; Guillaume Guérard
Hierarchical Clustering and Measure for Tourism Profiling Proceedings Article
Dans: 6th APWeb-WAIM International Joint Conference on Web and Big Data, p. 158-165, Nanjing, China, 2023.
@inproceedings{djebali_1936,
title = {Hierarchical Clustering and Measure for Tourism Profiling},
author = {Sonia Djebali and Quentin Gabot and Guillaume Guérard},
url = {https://link.springer.com/chapter/10.1007/978-3-031-25198-6_12},
year = {2023},
date = {2023-02-01},
booktitle = {6th APWeb-WAIM International Joint Conference on Web and Big Data},
volume = {13422},
pages = {158-165},
address = {Nanjing, China},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Flavien Deseure-Charron; Sonia Djebali; Guillaume Guérard
Clustering Method for Touristic Photographic Spots Recommendation Proceedings Article
Dans: 18th International Conference on Advanced Data Mining and Applications, Brisbane, Australia, 2022.
@inproceedings{deseure-charron_1935,
title = {Clustering Method for Touristic Photographic Spots Recommendation},
author = {Flavien Deseure-Charron and Sonia Djebali and Guillaume Guérard},
url = {https://link.springer.com/chapter/10.1007/978-3-031-22137-8_17},
year = {2022},
date = {2022-11-01},
booktitle = {18th International Conference on Advanced Data Mining and Applications},
address = {Brisbane, Australia},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Hugo Prevoteau; Sonia Djebali; Zhao Laiping; Nicolas Travers
Propagation Measure on Circulation Graphs for Tourism Behavior Analysis Proceedings Article
Dans: Bases de Données Avancées, Clermont-Ferrand, France, 2022.
@inproceedings{prevoteau_1921,
title = {Propagation Measure on Circulation Graphs for Tourism Behavior Analysis},
author = {Hugo Prevoteau and Sonia Djebali and Zhao Laiping and Nicolas Travers},
url = {https://bda2022.sciencesconf.org/resource/page/id/13},
year = {2022},
date = {2022-10-01},
booktitle = {Bases de Données Avancées},
address = {Clermont-Ferrand, France},
abstract = {Social network analysis has widespread in recent years, especially in digital tourism. Indeed the large amount of data that tourists produce during their travels represents an effective source to un- derstand their behavior and is of great importance for tourism stakeholders. This paper studies the propagation effect of tourists on the territory thanks to geotagged circulation graphs.
A new weighted measure is introduced for circulation charac- terization based on both topologies and distances. This measure helps to determine the behavior of tourists on local and global areas. An optimization strategy based on spanning trees is applied to reduce the computation on the whole graph while keeping a good approximation of the behavior.},
keywords = {},
pubstate = {online},
tppubtype = {inproceedings}
}
Hugo Prevoteau; Sonia Djebali; Zhao Laiping; Nicolas Travers
Propagation Measure on Circulation Graphs for Tourism Behavior Analysis Proceedings Article
Dans: ACM Symposium on Applied Computing, ACM, Brno, Czec Republic, 2022.
@inproceedings{prevoteau_1749,
title = {Propagation Measure on Circulation Graphs for Tourism Behavior Analysis},
author = {Hugo Prevoteau and Sonia Djebali and Zhao Laiping and Nicolas Travers},
url = {https://www.sigapp.org/sac/sac2022/index.html},
year = {2022},
date = {2022-04-01},
booktitle = {ACM Symposium on Applied Computing},
publisher = {ACM},
address = {Brno, Czec Republic},
abstract = {Social network analysis has widespread in recent years, especially in digital tourism. Indeed the large amount of data that tourists produce during their travels represents an effective source to understand their behavior and is of great importance for tourism stakeholders. This paper studies the propagation effect of tourists on the territory thanks to geotagged circulation graphs. Those graphs reflect traffic flows which need to be analyzed over time and space. A new weighted measure is introduced for circulation characterization based on both topologies and distances. This measure helps to determine the behavior of tourists on local and global areas. An optimization strategy based on spanning trees is applied to reduce the computation on the whole graph while keeping a good approximation of the behavior. The approach is simulated on various graphs and evaluated experimentaly over a real dataset at various geographic zones, scales, communities, and time.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Guillaume Guérard; Sonia Djebali; Quentin Gabot
Tourists Profiling by Interest Analysis Proceedings Article
Dans: International Conference on Advanced Data Mining and Applications, p. 42-53, Springer, Cham, Virtual, 2022, ISBN: 978-3-030-95407-9.
@inproceedings{guerard_1662,
title = {Tourists Profiling by Interest Analysis},
author = {Guillaume Guérard and Sonia Djebali and Quentin Gabot},
url = {https://link.springer.com/chapter/10.1007/978-3-030-95408-6_4},
issn = {978-3-030-95407-9},
year = {2022},
date = {2022-01-01},
booktitle = {International Conference on Advanced Data Mining and Applications},
volume = {13088},
pages = {42-53},
publisher = {Springer, Cham},
address = {Virtual},
abstract = {With the recent digital revolution, analyzing of tourists' behaviors
and research elds associated with it have changed profoundly.
It is now easier to examine behaviors of tourists using digital traces they
leave during their travels. The studies conducted on diverse aspects of
tourism focus on quantitative aspects of digital traces to reach its conclusions.
In this paper, we suggest a study focused on both qualitative and
quantitative aspect of digital traces to understand the dynamics governing
tourist behavior, especially those concerning attractions networks.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Guillaume Guérard; Sonia Djebali; Bi Chongke; Theo Demessance
Hidden Markov Model to Predict Tourists Visited Places Proceedings Article
Dans: Nick Koudas Vana Kalogeraki, Jianliang Xu (Ed.): 22nd IEEE International Conference on Mobile Data Management, p. 209-216, IEEE, virtual, 2021, ISBN: 978-1-6654-2845-3.
@inproceedings{guerard_1601,
title = {Hidden Markov Model to Predict Tourists Visited Places},
author = {Guillaume Guérard and Sonia Djebali and Bi Chongke and Theo Demessance},
editor = {Vana Kalogeraki, Nick Koudas, Jianliang Xu},
url = {https://ieeexplore.ieee.org/abstract/document/9474900},
issn = {978-1-6654-2845-3},
year = {2021},
date = {2021-06-01},
booktitle = {22nd IEEE International Conference on Mobile Data Management},
pages = {209-216},
publisher = {IEEE},
address = {virtual},
abstract = {Nowadays, social networks is become a popular means of analyzing tourist behavior, thanks to the digital traces left by travelers during their stays on these networks.
The massive amount of data generated by the propensity of tourists to share comments and photos during their trip makes it possible to model their journeys and analyze their behavior.
Predicting the next movement of tourist plays a key role in tourism marketing to understand demand and improve decision support.
In this paper, we propose a method to understand and to learn tourists' movements based on social network data analysis to predict the future movements. The method relies on a machine learning grammatical inference algorithm.
A major contribution in this paper is to adapt the grammatical inference algorithm to the context of big data.
Our method produces a hidden Markov model representing the movements of a group of tourists. The hidden Markov model is flexible and editable with new data.
The capital city of France, Paris is selected to demonstrate the efficiency of the proposed methodology.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Sonia Djebali; Guillaume Guérard; Laureen Deman; Quentin Boucher; Cedric Clastres
Bidding strategy of a seasonal storage and pump storage hydropower plants in reserve markets Proceedings Article
Dans: International Association for Energy Economics, virtual, 2021.
@inproceedings{djebali_1602,
title = {Bidding strategy of a seasonal storage and pump storage hydropower plants in reserve markets},
author = {Sonia Djebali and Guillaume Guérard and Laureen Deman and Quentin Boucher and Cedric Clastres},
url = {https://iaee2021online.org/download/contribution/fullpaper/1380/1380_fullpaper_20210614_063233.pdf},
year = {2021},
date = {2021-06-01},
booktitle = {International Association for Energy Economics},
address = {virtual},
abstract = {The increasing share of intermittent sources of energy will increase the need for frequency-control reserves. However, the current supply of reserves might decrease in the following years. The share of gas- and coal-fuel plants in the power mix is expected to decline in order to reduce greenhouse gas emissions. Hydropower technologies are often put forward as mature and low-carbon technologies able to contribute to cover this increasing need for reserves. Their flexibility and storage capability allow them to support the stable operation of the grid. The procurement of reserves being mostly market-based in Europe, the market design should send the correct price signals to encourage the participation in these markets.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Guillaume Guérard; Sonia Djebali
Tourism Management through the Big Data Paradigm Proceedings Article
Dans: David Chavalarias, Hocine Cherifi (Ed.): French Regional Conference on Complex Systems FRCCS, Springer - Applied Network Science Journal, virtual, 2021.
@inproceedings{guerard_1600,
title = {Tourism Management through the Big Data Paradigm},
author = {Guillaume Guérard and Sonia Djebali},
editor = {David Chavalarias, Hocine Cherifi},
url = {https://easychair.org/smart-program/FRCCS2021/},
year = {2021},
date = {2021-05-01},
booktitle = {French Regional Conference on Complex Systems FRCCS},
publisher = {Springer - Applied Network Science Journal},
address = {virtual},
abstract = {This paper highlights the two-ways relationship between data and entities producing or generating these data in the context of tourism management. Indeed, tourists leave various traces of their planning and trip on social media and networks. Moreover, studying those data to feed tourism marketing also affects the future data left by tourists. Understanding the intrinsic and extrinsic relationship between entities should significantly improve the knowledge in this research field.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Sonia Djebali; Nicolas Loas; Nicolas Travers
Indicators for Measuring Tourist Mobility Proceedings Article
Dans: International Conference on Web Information Systems Engineering, Amsterdam and Leiden, Netherlands, 2020, ISBN: 978-3-030-62004-2.
@inproceedings{djebali_1273,
title = {Indicators for Measuring Tourist Mobility},
author = {Sonia Djebali and Nicolas Loas and Nicolas Travers},
url = {http://wasp.cs.vu.nl/WISE2020/accept.html},
issn = {978-3-030-62004-2},
year = {2020},
date = {2020-10-01},
booktitle = {International Conference on Web Information Systems Engineering},
address = {Amsterdam and Leiden, Netherlands},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Sonia Djebali; Guillaume Guérard
Prédiction des comportements touristiques par minage des motifs et des règles séquentielles Proceedings Article
Dans: 21ème édition du congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Montpellier, France, 2020.
@inproceedings{djebali_1226,
title = {Prédiction des comportements touristiques par minage des motifs et des règles séquentielles},
author = {Sonia Djebali and Guillaume Guérard},
url = {https://roadef2020.sciencesconf.org/},
year = {2020},
date = {2020-02-01},
booktitle = {21ème édition du congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision},
address = {Montpellier, France},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Lillia Ben Baccar; Sonia Djebali; Guillaume Guérard
Tourist's Tour Prediction by Sequential Data Mining Approach Proceedings Article
Dans: Advanced Data Mining and Applications, 15th International Conference, ADMA 2019, p. pp. 681-695, Dalian, China, 2019, ISBN: ISBN 978-3-030-35230-1.
@inproceedings{ben_baccar_989,
title = {Tourist's Tour Prediction by Sequential Data Mining Approach},
author = {Lillia Ben Baccar and Sonia Djebali and Guillaume Guérard},
url = {https://link.springer.com/chapter/10.1007/978-3-030-35231-8_50},
issn = {ISBN 978-3-030-35230-1},
year = {2019},
date = {2019-11-01},
booktitle = {Advanced Data Mining and Applications, 15th International Conference, ADMA 2019},
pages = {pp. 681-695},
address = {Dalian, China},
abstract = {This paper answers the problem of predicting future behaviour tourist based on past behaviour of an individual tourist. The individual behaviour is naturally an indicator of the behaviour of other tourists. The prediction of tourists movement has a crucial role in tourism marketing to create demand and assist tourists in decision-making. With advances in information and communication technology, social media platforms generate data from millions of people from different countries during their travel. The main objective of this paper is to consider sequential data-mining methods to predict tourist movement based on Instagram data. Rules emerge from those ones are exploited to predict future behaviors. The originality of this approach is a combination between pattern mining to reduce the size of data and the automata to condense the rules. The capital city of France, Paris is selected to demonstrate the utility of the proposed methodology.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Thomas Raimbault; Abdellah Sabry; Sonia Djebali
Universal-endpoint.com : une plateforme d'accès simple au Web des Données Proceedings Article
Dans: EGC 2018, p. 475-478, Paris, France, 2018, ISBN: ISBN : 979-10-96289-07-3.
@inproceedings{raimbault_503,
title = {Universal-endpoint.com : une plateforme d'accès simple au Web des Données},
author = {Thomas Raimbault and Abdellah Sabry and Sonia Djebali},
url = {https://editions-rnti.fr/?procid=100174},
issn = {ISBN : 979-10-96289-07-3},
year = {2018},
date = {2018-01-01},
booktitle = {EGC 2018},
volume = {RNTI-E-34},
pages = {475-478},
address = {Paris, France},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Stéphane Loiseau; Sonia Djebali; Thomas Raimbault; Bérangère Branchet; Gaël Chareyron
Characterization of daily tourism behaviors based on place sequence analysis from photo sharing websites Proceedings Article
Dans: 2017 IEEE International Conference on Big Data, p. 2760 - 2765, Boston, USA, 2017, ISBN: ISBN: 978-1-5386-2714-3.
@inproceedings{loiseau_276,
title = {Characterization of daily tourism behaviors based on place sequence analysis from photo sharing websites},
author = {Stéphane Loiseau and Sonia Djebali and Thomas Raimbault and Bérangère Branchet and Gaël Chareyron},
url = {https://ieeexplore.ieee.org/document/8258241},
issn = {ISBN: 978-1-5386-2714-3},
year = {2017},
date = {2017-12-01},
booktitle = {2017 IEEE International Conference on Big Data},
pages = {2760 - 2765},
address = {Boston, USA},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Thomas Raimbault; Sonia Djebali
Interroger intuitivement le Web des Données avec SimplePARQL Proceedings Article
Dans: Conférence Nationale sur les Applications Pratiques de l'Intelligence Artificielle, Caen, France, 2017.
@inproceedings{raimbault_286,
title = {Interroger intuitivement le Web des Données avec SimplePARQL},
author = {Thomas Raimbault and Sonia Djebali},
url = {https://pfia2017.greyc.fr/apia/programme},
year = {2017},
date = {2017-07-01},
booktitle = {Conférence Nationale sur les Applications Pratiques de l'Intelligence Artificielle},
address = {Caen, France},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Sonia Djebali; Thomas Raimbault
Regrouper des résultats SPARQL par comparaison de leurs contenus tels qu'ils sont agencés dans la base RDF interrogée Proceedings Article
Dans: CORIA, Marseille, France, 2017.
@inproceedings{djebali_280,
title = {Regrouper des résultats SPARQL par comparaison de leurs contenus tels qu'ils sont agencés dans la base RDF interrogée},
author = {Sonia Djebali and Thomas Raimbault},
url = {http://www.asso-aria.org/coria/2017/papers/coria.2017.9/},
year = {2017},
date = {2017-03-01},
booktitle = {CORIA},
address = {Marseille, France},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Guillaume Guérard; Sonia Djebali
Rendre 'intelligent' le Smart Grid Proceedings Article
Dans: 18ème conférence annuelle de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Metz, France, 2017.
@inproceedings{guerard_272,
title = {Rendre 'intelligent' le Smart Grid},
author = {Guillaume Guérard and Sonia Djebali},
url = {http://roadef2017.event.univ-lorraine.fr/index.html},
year = {2017},
date = {2017-02-01},
booktitle = {18ème conférence annuelle de la Société Française de Recherche Opérationnelle et d'Aide à la Décision},
address = {Metz, France},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Sonia Djebali; Thomas Raimbault
SimplePARQL: a new approach using keywords over SPARQL to query the web of data Proceedings Article
Dans: Proceedings of the Posters and Demos Track of 11th International Conference on Semantic Systems - SEMANTiCS2015, p. p43, Vienna, Austria, 2015.
@inproceedings{djebali_388,
title = {SimplePARQL: a new approach using keywords over SPARQL to query the web of data},
author = {Sonia Djebali and Thomas Raimbault},
url = {http://ceur-ws.org/Vol-1481/},
year = {2015},
date = {2015-09-01},
booktitle = {Proceedings of the Posters and Demos Track of 11th International Conference on Semantic Systems - SEMANTiCS2015},
volume = {1481},
pages = {p43},
address = {Vienna, Austria},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Guillaume Guérard; Sonia Djebali
Can We Trust AI in Medicine? The Hidden Biases in Healthcare Data Divers
LinkedinPulse, 2025.
@misc{guerard_3546,
title = {Can We Trust AI in Medicine? The Hidden Biases in Healthcare Data},
author = {Guillaume Guérard and Sonia Djebali},
url = {https://www.linkedin.com/pulse/can-we-trust-ai-medicine-hidden-biases-healthcare-data-gu%25C3%25A9rard-kd01e/},
year = {2025},
date = {2025-03-01},
howpublished = {LinkedinPulse},
keywords = {},
pubstate = {online},
tppubtype = {misc}
}
Guillaume Guérard; Sonia Djebali
Decoding Cancer: How AI and Genetics Work Together to Save Lives Divers
LinkedinPulse, 2025.
@misc{guerard_3547,
title = {Decoding Cancer: How AI and Genetics Work Together to Save Lives},
author = {Guillaume Guérard and Sonia Djebali},
url = {https://www.linkedin.com/pulse/decoding-cancer-how-ai-genetics-work-together-save-lives-gu%25C3%25A9rard-nesme/},
year = {2025},
date = {2025-03-01},
howpublished = {LinkedinPulse},
keywords = {},
pubstate = {online},
tppubtype = {misc}
}
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