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Ph.D de

Ph.D
Group : Artificial Intelligence and Inference Systems

XSEARCH, un moteur de recherche pour XML combinant la structure et le contenu

Starts on 01/09/2002
Advisor : ROUSSET, Marie-Christine

Funding : Autre financement à préciser
Affiliation : Université Paris-Saclay
Laboratory : Univ. Hébraïque de Jérusalem

Defended on 30/09/2005, committee :
Serge Abiteboul
Catherine Berrut
Patrick Gallinari
Marie-Christine Rousset
Anne-Marie Vercoustre

Research activities :
   - Semantic Web
   - XML

Abstract :
This thesis work focused on information retrieval from semi-structured data and on the development of a search engine for XML data.

Ph.D. dissertations & Faculty habilitations
MICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACES
The topic of this habilitation is the study of very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. For several years, together with my collaborators, I have been studying human perception, interaction, and analysis with micro visualizations in multiple contexts. In this document I bring together three of my research streams related to micro visualizations: data glyphs, where my joint research focused on studying the perception of small-multiple micro visualizations, word-scale visualizations, where my joint research focused on small visualizations embedded in text-documents, and small mobile data visualizations for smartwatches or fitness trackers. I consider these types of small visualizations together under the umbrella term ``micro visualizations.'' Micro visualizations are useful in multiple visualization contexts and I have been working towards a better understanding of the complexities involved in designing and using micro visualizations. Here, I define the term micro visualization, summarize my own and other past research and design guidelines and outline several design spaces for different types of micro visualizations based on some of the work I was involved in since my PhD.

A NEW GENERATION OF GRAPH NEURAL NETWORKS TO TACKLE AMORPHOUS MATERIALS


SPOTTING NEURAL NETWORK BOTTLENECKS AND FIXING THEM BY ARCHITECTURE GROWTH