Gaël Chareyron

@inproceedings{Dupuis2019,

title = {RTIM: a Real-Time Influence Maximization Strategy},

author = {David Dupuis and Cédric du Mouza and Nicolas Travers and Gaël Chareyron},

year  = {2019},

date = {2019-11-26},

booktitle = {International Conference on Web Information Systems Engineering (WISE'19)},

publisher = {Springer},

abstract = {Influence Maximization (IM) is a well studied maximum coverage problem, which consists in finding in a network the top-k influ- encers who will maximize the diffusion of a piece of information. It is commonly associated with basic online advertising strategies. However, today, the exponential growth of online advertising is due to Real-Time Bidding (RTB) which allows advertising agen- cies to target specific users with specific ads on specific webpages. It requires complex ad placement decisions in real-time to face a high-speed stream of online users. In order to stay relevant, the IM problem should be updated to answer RTB needs. While most tra- ditional IM methods generate a static set of top-k influencers, they do not deal with the topic of influence maximization in a real-time bidding environment which requires dynamic influence targeting.

This paper studies this topic and proposes RTIM, the first IM al- gorithm capable of taking influence maximization decisions within a real-time bidding environment. We also analyze influence scores of users in several social networks in order to show their impact in our approach. Finally, we offer a thorough experimental process to compare static versus dynamic IM solutions wrt. influence scores.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Chareyron2019b,

title = {Tourism Analysis on Graphs with Neo4Tourism},

author = {Gaël Chareyron and Ugo Quelhas and Nicolas Travers},

year  = {2019},

date = {2019-11-26},

booktitle = {International Conference on Web Information Systems Engineering (WISE'19)},

address = {Hong Kong, China},

abstract = {Tourists’ behavior analysis has become a popular mean with Digital Tourism. Traditional ground studies has been extended with mas- sive data analysis to confront models. Tourism actors are faced with the need to deeply understand tourists’ circulation both quantitively and qualitatively. Thus, the challenge is to deal with data from tourist ori- ented social networks by integrating huge volumes of data. We propose in this paper the Neo4Tourism framework based on a graph data model specialized in digital tourism analysis. Our model is dedicated to tourists’ circulation and aims at simulating tourists’ behavior. In this demonstra- tion we discuss how our system 1) integrates data from TripAdvisor in a Neo4j graph database, 2) produces circulation graphs, 3) enhances graphs manipulations and deep tourists’ analysis with centrality.

},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Chareyron2019bb,

title = {Neo4Tourism - A framework for Graph Data Analysis on Tourism},

author = {Gaël Chareyron and Ugo Quelhas and Nicolas Travers},

year  = {2019},

date = {2019-10-17},

booktitle = {Bases de Données Avancées (BDA'19)},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Dupuis2019b,

title = {Influence Maximization in a Real-Time Bidding Environment},

author = {David Dupuis and Cédric du Mouza and Nicolas Travers and Gaël Chareyron},

year  = {2019},

date = {2019-10-17},

booktitle = {Bases de Données Avancées (BDA'19)},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Charey2017d,

title = {Characterization of daily tourism behaviors based on place sequence analysis from photo sharing websites},

author = {Loiseau, T.J. and Djebali, S. and Raimbault, T. and Branchet, B. and Chareyron, G. },

year  = {2017},

date = {2017-12-30},

booktitle = {IEEE Big Data 2017, Boston, USA, 11-14 décembre},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ChareyronIEEE2015,

title = {A new area tourist ranking method},

author = {Gaël Chareyron and Berengère Branchet and Sébastien Jacquot},

year  = {2015},

date = {2015-10-29},

booktitle = {IEEE Big Data 2015},

address = {Santa-Clara, CA, USA},

organization = {IEEE},

abstract = {This paper proposes a new method to classify tourist

areas following specific characteristics. Indeed, we introduce

some original computed indicators using social networks and

administrative data. These 10 indicators are used to construct

tourist area’s profiles.We demonstrate in this paper that different

tourist spots can then be grouped according to their profiles. Thus

we present an original area tourist ranking method based on big

data analysis.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{CDR14,

title = {Big Data: a new challenge for tourism},

author = { Gaël Chareyron and Jérôme Da-Rugna and Thomas Raimbault},

url = {http://labs.esilv.fr/publications/public/2014/CDR14},

year  = {2014},

date = {2014-01-01},

booktitle = {IEEE International Conference on Big Data, 2014},

abstract = {This paper proposes the foundations for a definition of digital tourist survey field based on the study of social networks. Several social network provide essential information on the perceptions of tourist destination. Nevertheless to operate correctly, several points should be discussed. This article provides multiple ideas for reflections on the challenges and opportunities offered by these new media.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{PC14,

title = {Co-producer tourists: the geographical imaginary of Colombian cities.},

author = { Sairi Piñeros and Gaël Chareyron},

url = {http://labs.esilv.fr/publications/public/2014/PC14},

year  = {2014},

date = {2014-01-01},

booktitle = {RGS-IBG Annual International Conference 2014},

abstract = {Since 1980s, the USA, UK and EU Travel Warnings have alerted tourists about travel risks when visiting Colombian cities. Thenceforth, both alerts and risk imaginaries have remained in the minds of people. Today, the potential tourists to visit in Colombia usually seek information on the internet, finding different sources such as travel blogs, forums, photos and travel communities advices. This material from tourists, who have already traveled, will affect potential tourists beliefs. Likewise, tourists co-produce signals which influence places geographical imaginaries and urban beliefs. The objective of this poster is to present the progress of the PhD research exploration phase. Photos and broadcast media texts have been extracted, spatialized and analyzed. This information will help to understand the new technologies role on tourists experiences diffusion, in the case of cities affected by negative imaginaries.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{RCK14,

title = {Cognitive Map of Tourist Behavior based on Tripadvisor},

author = { Thomas Raimbault and Gaël Chareyron and Corinne Krzyzanowski-Guillot},

url = {http://labs.esilv.fr/publications/public/2014/RCK14},

year  = {2014},

date = {2014-01-01},

booktitle = {IEEE International Conference on Big Data, 2014},

abstract = {The objective of this paper is to identify, based on big data from Tripadvisor, tourist behavior in how users rate a tourist place. Firstly, we propose different correspondence analyses (CA) on data from Tripadvisor to discover pairwise dependences between data properties (e.g. rating vs. place type, age vs. country). Secondly, we merge and map all our CA results as a cognitive map, both to bring out and understand influences between the studied concepts and to make easier human visualization.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{CCDBBM14,

title = {Du vélo au chateau. La diversité des pratiques et des imaginaires touristiques dans l'espace rural de la Touraine et du Blèsois.},

author = { Saskia Cousin and Gaël Chareyron and Jérôme Da-Rugna and Berengère Branchet and Dominique Bachelart and Maxime Michaud},

url = {http://labs.esilv.fr/publications/public/2014/CCDBBM14},

year  = {2014},

date = {2014-01-01},

booktitle = {Colloque Pratiques touristiques, discours et représentations autour des usages contemporains de la ruralité – Ningbo (Chine)},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DMBTWCD14,

title = {Flickr Trace Summarization: from Images to Imaginary},

author = { Laurent Daireaux and Vincent Mallard and Berengère Branchet and Martin Tardy and Maxime Wasselin and Gaël Chareyron and Jérôme Da-Rugna},

url = {http://labs.esilv.fr/publications/public/2014/DMBTWCD14},

year  = {2014},

date = {2014-01-01},

organization = {IEEE},

series = {IEEE 18th International Conference on Intelligent Engineering Systems 2014 (INES 2014)},

abstract = {Stakeholders of tourism and science of tourism request tools to understand and analyze the tourist practices and tourist mobility. While these ones are still only partially known, the rise of image hosting websites opens a new trend to follow. This new source of information allows to apprehend frequentation of a tourist site according to seasons, years, photographer country of origin. Furthermore whatever the site size : city, county, country, continent or any delimited area. Focusing on a specific destination, the set of user photos characterizes his path and the items that illustrate, from his point of view, the destination. In this paper we propose a new methodology to automatically build path visual description from image hosting websites. To describe visually a path, a clustering process provides the most-representative images for each point of interest along the path. To illustrate how this work permits inference of imaginary, we present our results on New-York city.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{BCDJ14,

title = {Le partage des expériences culinaires via les réseaux sociaux dans les destinations touristiques gastronomiques (Barcelone, Paris, Florence, Lyon)},

author = { Berengère Branchet and Gaël Chareyron and Jérôme Da-Rugna and Sébastien Jacquot},

url = {http://labs.esilv.fr/publications/public/2014/BCDJ14},

year  = {2014},

date = {2014-01-01},

booktitle = {International Conference UNITWIN UNESCO Chair “Culture, Tourism, Development” Tourism and Gastronomy Heritage: Foodscapes, Gastroregions and Gastronomy Tourism},

abstract = {Cette proposition vise à étudier les modalités de partage et mise en scène des expériences culinaires via les réseaux sociaux, dans des destinations touristiques qui mettent en avant leur patrimoine gastronomique ou traditions culinaires (Barcelone, Paris, Florence, Lyon), par la collecte et analyse automatisée des évaluations et photos sur Tripadvisor et Instagram.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{CDG14,

title = {Opportunities & challenges of tourist data mining.},

author = { Gaël Chareyron and Jérôme Da-Rugna and Daniel Gabay},

editor = {Ninth International Conference on Interdisciplinary Social Sciences},

url = {http://labs.esilv.fr/publications/public/2014/CDG14},

year  = {2014},

date = {2014-01-01},

address = {Vancouver (Canada)},

abstract = {It is relatively easy to represent these footprints with density maps, which illustrate the main areas of touristic interest, and to produce them at various space scales and time seasons. But a more interesting approach is to analyze the trajectories of tourists at an individual level, a possibility offered by the way websites are structured. For instance we can interpolate the trip of a tourist in a city in a day, or in a given region for a longer vacation and even the various countries he has visited in recent years. Key to this approach is the construction of a large scale data matrix describing when a given photographer has visited a prescribed geographical site. By aggregation of the photographs in our sample (which can also distinguish characteristics such as citizenship, age, social status...), we thus obtain more detailed and robust frequentation statistics. Moreover we can construct graphs showing the similarity links between touristic sites or between photographers categories. We devote a considerable effort to algorithmic developments for clustering efficiently our dataset and reducing the dimension of our analysis. We report some of our results on a case study of the Loire Valley in central France, a UNESCO World Heritage site and discuss the further potential of our research for regional touristic policy improvement as well as for trip planning advices for individual tourists},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{CDCM14,

title = {Quand les touristes deviennent agence de voyages. La creation d une application collaborative},

author = { Gaël Chareyron and Jérôme Da-Rugna and Saskia Cousin and Maxime Michaud},

url = {http://labs.esilv.fr/publications/public/2014/CDCM14},

year  = {2014},

date = {2014-01-01},

booktitle = {Ludovia},

note = {http://www.ludovia.com/2014/07/quand-les-touristes-deviennent-agence-de-voyages-la-creation-dune-application-collaborative/},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{BCD14,

title = {R et apprentissage : analyse de comportement touristique à partir de données géographiques géotaggées},

author = { Berengère Branchet and Gaël Chareyron and Jérôme Da-Rugna},

url = {http://labs.esilv.fr/publications/public/2014/BCD14},

year  = {2014},

date = {2014-01-01},

booktitle = {LMCS},

series = {Journée nationale pour la modélisation et la simulation 0D/1D},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{CCDGJ13,

title = {Images de la métropole},

author = { Gaël Chareyron and Saskia Cousin and Jérôme Da-Rugna and Daniel Gabay and Sébastien Jacquot},

url = {http://der3i.labs.esilv.fr/publications/public/2013/CCDGJ13},

year  = {2013},

date = {2013-01-01},

booktitle = {Les imaginaires de la métropole créative - Les médias de la métropole, de l’écriture à l’espace public},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{CDB13,

title = {Mining tourist routes using flickr traces},

author = { Gaël Chareyron and Jérôme Da-Rugna and Berengère Branchet},

url = {http://der3i.labs.esilv.fr/publications/public/2013/CDB13},

year  = {2013},

date = {2013-01-01},

booktitle = {FOSINT-SI 2013 International Symposium on Foundations of Open Source Intelligence and Security Informatics - IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}