Please find below the announcement of a postdoctoral position in the
University of La Rochelle, France.
If you have a Ph.D in computer science and you have working knowledge in
the fields of NLP, IR, Big data and/or ontologies, and if you like the
idea of joining a dynamic research group that lies within walking
distances of 3 different beaches, please let us know!
Please note the short deadline: 1 December 2014!!
(apologies for cross-posting)
http://l3i.univ-larochelle.fr/IMG/siteon0.png?1393854390Post‐Doctoral
Positionhttp://www.univ-larochelle.fr/IMG/siteon0.png?1388676535
Spatiotemporal analysis of touristic events
The L3i laboratory, within the Tourinflux project
(http://www.tourinflux.com/) is seeking a postdoctoral researcher in
computer science, on the topic of the spatiotemporal analysis of
touristic events.
Length: 14 months
Expected recruitment: 1stof January 2015
Net salary: 2100 € monthly
Location: L3i laboratory, La Rochelle, France
Fields: Computer Science / Semantic Web / Natural Language Processing
Keywords: E-tourism, spatiotemporal events, NLP, Normalisation
(schema.org, TourInFrance), Semantic Web, Data analysis
Job description:
The work will be conducted in the informatics, image and interaction
laboratory (L3i), within the Tourinflux project, supported by funding
from a program of “investment for the future“ (PIA). The L3i is a
120-person laboratory created in 1993. Hosted in the historical and
sunny city of La Rochelle (http://www.holidays-la-rochelle.co.uk/), it
is ranked A by the French research evaluation agency (AERES).
In addition to the L3i, the Tourinflux project involves 2 companies and
an association of companies, in collaboration with several actors of the
French tourism industry. The project aims at providing the tourism
industry with with a set of tools allowing them to handle both their
internal data, and the information available on the Web, so as to better
diagnose and influence on the perception of territories. The tools
currently available are insufficient, and a lot of the data gathering,
analysis and processing is currently done by hand, or via the use of
various partially adequate tools. Tourinflux aims to provide an
extensive dashboard, allowing all institutions, whatever their size, to
visualize and interprete the information available about their
territory. This should allow them to improve their decision process and
subsequently, their effectiveness.
Specifically, this postdoctoral position will be focused on the analysis
and the representation of touristic events within a knowledge base. A
first step was already completed, allowing to analyze texts in natural
language, so as to grasp the opening hours of touristic objects. It is
now time to enrich and contextualize the text mark-up, so as to
structure the data and let it be usable within the main process of
Tourinflux. A phase of modeling and standardizing of the representation
schemas of touristic objects is already engaged. The postdoctoral work
will consist in two main tasks:
1.
Semi-automated semantic-based structuration of tourist information:
Tourism information is both heterogeneous (free text, Web page,
pictures, …) and semi-structured. Structuring information is a major
challenge at a time when the masses of unstructured information are
constantly evolving, be it on the Web or within organisations. The
classical processes of information structuring are manual or
semi-automated, strongly dependent on the domain and its semantics. The
applicant is to set up a semi-automated process for structuring
touristic information. Two key challenges were identified:
*
Adapting NLP techniques to the specific domain of tourism
information, and extract the key features of the field
*
Model the semantics of the domain, which seems to naturally fit a
hierarchical structure, such as that of a thesaurus or an ontology
2.
Vertical search for tourism professionals
At first, a “classic” query-based information retrieval system is to be
built. Next, further strategies shall be considered, exploiting the
structure of the data set (logical as well as semantic). Faceted
information retrieval seems to be one promising line of work, allowing
the user to express an information need and then refine it through her
browsing. Such mechanisms facilitate query refinement, which seems
especially appropriate for the vertical search of tourism professional.
The goals of this IR task are the following:
o
To determine the minimal features of each touristic object, for
faster information access. Both a statistical and logical
approach can be envisaged, as well as a hybrid method.
o
To set up the prototype of a faceted IR system, adapted to the
specific needs of tourism professionals.
Specific requirements:
Candidates must have Ph.D. in computer science, with abilities in
knowledge representation and data mining. Research experience is also
required in at least 2 of the following domains:
*
Natural Language Processing, Text mining
*
Information Retrieval
*
Big Data and Data Warehouses (eg, Hadoop)
*
Modeling, Ontologies and inference engines
*
Annotation and Evaluation methodologies
*
Writing extraction grammars
General requirements:
*
One or more of the following programming languages: Python, C/C++, java…
*
Team-work skills (knowledge of Agile methodologies would be a plus)
*
Proven ability for scientific writing
To apply:
All candidates are required to send a resume, an expression of interest,
and the names and contact information of at least 2 references
(including email adresses) to:
[email protected]
[email protected]
[email protected]
[email protected]
Please note that applications must be sent at the latest on Monday 1
December
--
Antoine Doucet
Full Professor
L3i - Laboratoire Informatique, Image et Interaction
University of La Rochelle - IUT de La Rochelle
https://doucet.users.greyc.fr/
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