Brigitte Trousse
Contact address
INRIA Sophia
Antipolis
AxIS Research Project-Team
2004, Route Des Lucioles BP93
06902 Sophia Antipolis Cedex
France
Tel:+33 4 92 38 77 45 |
E-mail:Brigitte.Trousse@inria.fr
Personnal Page
In General
I hold a Ph.D. in Computer Science (1989, Artificial Intelligence and
Computer-Aided Design), a D.E.S.S diploma in Software Engineering (1985), and a
Master degree in Mathematics (1980), all from the University
of Nice-Sophia-Antipolis , France.
I was belonging in the permanent staff of
INRIA Sophia-Antipolis from 1990. After being a member of the SECOIA team
(ex-SMECI team) then the scientific leader of the AID Research team
(Artificial Intelligence and Design Group) of INRIA-Sophia Antipolis (French
National Institute for Research in Computer Science and Control), I was the
scientific leader of the AxIS
research-project Team (november 2001,
end of 2013). Before belonging to the permanent staff of INRIA, i held a
post-doctoral research position (1990) at the SECOIA team and a PH-D student
position (1987-1989) at the SMECI team at INRIA Sophia-Antipolis.
And before joining INRIA, I held a permanent
Professor position of Mathematics in a High School in Nice (1980-1984), having
a teaching degree in Mathematics and Physical Education for High Schools in
Nice (France, 1980).
Publications
For the list of all my
publications, click
here
Google scholar : citations researchgate : here
Zoom of three contributions
1.
M. Jaczynski
and B. Trousse. BROADWAY : A World
Wide Web Browsing Advisor Reusing Past Navigations from a Group of Users. In Proceedings
of the Third UK Case-Based
Reasoning Workshop (UKCBR3), Manchester, UK, September 9, 1997.
Topic (Case Based
Reasoning, Web
search) : linked to Jaczynski’s thesis on CBR, reuse of time-extended
situations. Development of the Broadway approach for personalised support
tools for Web information browsing
and search +
CBR*tools the first object-oriented framework in CBR (based on Gamma design
patterns). Many applications and contracts
2. D. Tanasa,
B. Trousse. Advanced
Data Preprocessing for Intersites Web Usage Mining,
in: IEEE Intelligent Systems, 19(2), p. 59–65, 2004.
Topic (Web usage mining): linked to tanasa’s thesis, the second thesis adressing Web Log preprocessing after Cooley’one (2000), many applications and contracts
3. B. Trousse, C. Tiffon, M.
Pallot. Co-creating
Environmental Services based on Pollution Citizen Sensing. Interdisciplinary Studies Journal
- Vol 3, Number 4, 2014, Laurea
University of Applied Sciences.
Topic (Living Lab,
UX model, data mining)–
article reporting MyGreenservices
(MGS), a sucessful and original project
based on the Living Lab approach related to Air Quality and Noise in 2010-2013 (realised during the FP7 Elliot collaborative project). This project was also a good illustration of what is a living lab process with
two cycles of the design of MGS platform and of the value co-creation
by citizen. Finally it was a research-action
project with the definition of a new Ideation method (dedicated to IoT based services), the
definition of an hybrid
model for measuring UX based
on an ethnographical and usage mining
approach and
more classically it provided a new applicative context
offering the validation/application of some AxIS researches
on data mining methods
Research Interests
Until 2001 : Artificial Intelligence and Design,
(Re)Design of Adaptive Web sites,
Adaptive Recommender Systems, Web
Usage Mining, Case-based reasoning,
Constraint-based programming, Web Semantics, Computer-Supported Cooperative
Work, Viepwoint Managment in Design of Complex systems, Argumentative and
topoi-based reasoning
Human
interfaces, Recommendations for supporting
Search and Navigation on the Web
and within an Information systems
And
applications of the above on the Web and for design groupware.
For
the AID publications until 2001, click
here.
After 2001 : Usage mining, Web usage mining, Web Log preprocessing, Data Mining, Hierarchical Clustering,
Sequential pattern extraction, ontologies & data mining (Rationale in
decision making), Hybrid Usage Mining (mixing ontologies & ethnography
& data mining) applied in various applications, design of user centered Web tools for supporting
transportation, ideation methods, user experience analysis, analysis of
behaviour changes, research on living labs, smart cities…
Last
modified: Wed Oct 13 15:05:54 MEST 2004