Jérôme Champavère
French Institute for Research in Computer Science and Automation
7 Papers
39 Citations
Jérôme Champavère is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Tree (set theory) & Information extraction. The author has an hindex of 5, co-authored 7 publications. Previous affiliations of Jérôme Champavère include university of lille & Laboratoire d'Informatique Fondamentale de Lille.
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Papers
Efficient inclusion checking for deterministic tree automata and XML Schemas
Jérôme Champavère,Rémi Gilleron,Aurélien Lemay,Joachim Niehren +3 more
- 01 Nov 2009
TL;DR: These algorithms for testing inclusion of automata for unranked trees A in deterministic DTDs or deterministic EDTDs with restrained competition D in time O(|A|.|@S|).
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Efficient Inclusion Checking for Deterministic Tree Automata and DTDs
Jérôme Champavère,Rémi Gilleron,Aurélien Lemay,Joachim Niehren +3 more
- 01 Jun 2008
TL;DR: This work presents a new algorithm for testing language inclusion L(A) ⊆ L(B) between tree automata in time O(|A|*|B|) where Bis deterministic.
Modeling Tree Structures, Machine Learning, and Information Extraction
Rémi Gilleron,Joachim Niehren,Karine Lewandowski,Anne-Cécile Caron,Aurélien Lemay,Yves Roos,Isabelle Tellier,Sophie Tison,Marc Tommasi,Fabien Torre,Mathias Samuelides,Sławek Staworko,Lingbo Kong,Florent Jousse,Patrick Marty,Jérôme Champavère,Emmanuel Filiot,Olivier Gauwin,Édouard Gilbert,Damien Poirier,Matthieu Keith,Hanh-Missi Tran,Feriel Lahlali +22 more
- 01 Jan 2007
TL;DR: This project wants to incorporate novel approaches for modeling tree structure and emerging techniques for machine learning into adaptive information extraction systems for the Web.
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•Journal Article
Query induction with schema-guided pruning strategies
TL;DR: This work distinguishes the class of regular queries that are stable under a given schemaguided pruning strategy, and shows that this class is learnable with polynomial time and data.
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Schema-Guided Induction of Monadic Queries
Jérôme Champavère,Rémi Gilleron,Aurélien Lemay,Joachim Niehren +3 more
- 22 Sep 2008
TL;DR: This work shows how to integrate schema guidance into an RPNI-based learning algorithm, in which monadic queries are represented by pruning node selecting tree transducers, and presents experimental results on schema guidance by the DTD of HTML.