C
Claire David
Researcher at University of Paris
Publications - 66
Citations - 833
Claire David is an academic researcher from University of Paris. The author has contributed to research in topics: Finite difference & Sierpinski triangle. The author has an hindex of 10, co-authored 63 publications receiving 779 citations. Previous affiliations of Claire David include Pierre-and-Marie-Curie University.
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Proceedings ArticleDOI
Two-Variable Logic on Words with Data
TL;DR: It is shown that satisfiability for the two-variable first-order logic FO2(~,<,+1) is decidable over finite and over infinite data words, where ~ is a binary predicate testing the data value equality and +1,< are the usual successor and order predicates.
Journal ArticleDOI
Two-variable logic on data words
TL;DR: This article shows that satisfiability for the two-variable fragment FO2(∼,<,+1) of first-order logic with data equality test ∼ is decidable over finite and infinite data words.
Proceedings ArticleDOI
Two-variable logic on data trees and XML reasoning
TL;DR: It is shown that satisfiability for two-variable first-order logic is decidable if the tree structure can be accessed only through the child and the next sibling predicates and the access to data values is restricted to equality tests.
Journal ArticleDOI
On solitary wave solutions of the compound Burgers–Korteweg–de Vries equation
TL;DR: In this paper, the first integral method based on ring theory in commutative algebra for the compound Burgers-Korteweg-de Vries equation was proposed, and several new kink-profile waves and periodic waves were established.
Journal ArticleDOI
Research Directions for Principles of Data Management (Abridged)
Serge Abiteboul,Marcelo Arenas,Pablo Barceló,Meghyn Bienvenu,Diego Calvanese,Claire David,Richard Hull,Eyke Hüllermeier,Benny Kimelfeld,Leonid Libkin,Wim Martens,Tova Milo,Filip Murlak,Frank Neven,Magdalena Ortiz,Thomas Schwentick,Julia Stoyanovich,Jianwen Su,Dan Suciu,Victor Vianu,Ke Yi +20 more
TL;DR: The report organizes the identified research challenges for PDM around seven core themes, namely Managing Data at Scale, Multi-model Data, Uncertain Information, Knowledge-enriched Data, Data Management and Machine Learning, Process and Data, and Ethics and Data Management.