Christian Sallaberry

Dr. Christian Sallaberry

LIUPPA lab., University of Pau and Pays Adour, 64000 Pau, France

Research Focus & Metrics

Academic Career Length

35Years (1992-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 November 2007 in Journal of Visual Languages & Computing
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Journal Article
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MGMauro Gaio
Mauro Gaio
CSChristian Sallaberry
Christian Sallaberry
PEPatrick Etcheverry
Patrick Etcheverry
CMChristophe Marquesuzaa
Christophe Marquesuzaa
JLJulien Lesbegueries
Julien Lesbegueries

30 June 2007 in Document numérique
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Journal Article
Closed access
APAnnig Le Parc-Lacayrelle
Annig Le Parc-Lacayrelle
MGMauro Gaio
Mauro Gaio
CSChristian Sallaberry
Christian Sallaberry
La composante temps dans l'information géographique textuelle. Extraction et recherche d'information dans des fonds documentaires patrimoniaux numérisés

1 June 2010 in International Journal on Digital Libraries
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Journal Article
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DPDamien Palacio
Damien Palacio
GCGuillaume Cabanac
Guillaume Cabanac
CSChristian Sallaberry
Christian Sallaberry
GHGilles Hubert
Gilles Hubert

Verified
Journal Article
Open access
PDF file
CCCécile Cayèré
Cécile Cayèré
CSChristian Sallaberry
Christian Sallaberry
FCFaucher Cyril
Faucher Cyril
MBMarie-Noëlle Bessagnet
Marie-Noëlle Bessagnet
Philippe RoosePhilippe Roose
Philippe Roose
RJRichard Jérémy
Richard Jérémy
Here we design a semantic trajectory model responding to specific needs expressed by tourism analyst experts. Thus, this model takes into account: (i) the description of sequences of imbricated semantic segments, (ii) the definition of enrichment data integrating spatial, temporal and thematic dimensions and (iii) the association of such data with positions or with trajectory segments. Each of these features is necessary for the processing and analysis of tourist mobility data, which we will detail. For validation purposes, we experiment our model on two outdoor mobility track scenarios computed in a processing chain. We also show that our model is generic and extensible thanks to two other scenarios on different datasets.

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Journal Article
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LRLandy Rajaonarivo
Landy Rajaonarivo
André FontelesAndré Fonteles
André Fonteles
CSChristian Sallaberry
Christian Sallaberry
MBMarie-Noëlle Bessagnet
Marie-Noëlle Bessagnet
Philippe RoosePhilippe Roose
Philippe Roose
QCQuentin Coudert
Quentin Coudert
The cultural heritage of a region, be it a highly visited one or not, is a formidable asset for the promotion of its tourism. In many places around the world, an important part of this cultural heritage has been catalogued by initiatives backed by governments and organisations. However, as of today, most of this data has been mostly unknown, or of difficult access, to the general public. In this paper, we present research that aims to leverage this data to promote tourism. Our first field of application focuses on the French Pyrenees. In order to achieve our goal, we worked on two fronts: (i) the ability to export this data from their original databases and data models to well-known open data platforms; and (ii) the proposition of an open-source algorithm and framework capable of recommending a sequence of cultural heritage points of interests (POIs) to be visited by tourists. This itinerary recommendation approach is original in many aspects: it not only considers the user preferences and popularity of POIs, but it also integrates different contextual information about the user as well as the relevance of specific sequences of POIs (strong links between POIs). The ability to export the cultural heritage data as open data and to recommend sequences of POIs are being integrated in a first prototype.

29 October 2008
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Conference Paper
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PDF file
CSChristian Sallaberry
Christian Sallaberry
MGMauro Gaio
Mauro Gaio
DPDamien Palacio
Damien Palacio
JLJulien Lesbegueries
Julien Lesbegueries