Ph.D
Group : Artificial Intelligence and Inference Systems

Recherche ciblée de documents sur le Web

Starts on 01/10/2001
Advisor : ROUSSET, Marie-Christine

Funding : A
Affiliation : Université Paris-Saclay
Laboratory : Orsay

Defended on 08/06/2005, committee :

Research activities :
   - Artificial Intelligence
   - Semantic Web

Abstract :
Our work combines a search engine such as Google or a Web crawler (such as that of Xyleme) with a filtering tool that can distinguish, among the possible thousands of web pages returned by Google or the Xyleme Crawler, those that really contain useful data for the datawarehouse. In the first e.dot experiments, it was shown that guiding the search through the web by keywords extracted from the domain ontology was not precise enough to guarantee that the returned Web pages were relevant to the topic of the warehouse. Our approach for designing a filtering tool is generic and declarative. We have defined and implemented a query language, called WebQueL, which anables the combination of different criteria for specifying the web pages of interest. Those criteria allow for combining content and structure of searched documents.

CAUSAL LEARNING FOR DIAGNOSTIC SUPPORT


CAUSAL UNCERTAINTY QUANTIFICATION UNDER PARTIAL KNOWLEDGE AND LOW DATA REGIMES


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.