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Dive into the research topics where Cécile Fabre is active.

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Featured researches published by Cécile Fabre.


conference on computational natural language learning | 2000

Inductive logic programming for corpus-based acquisition of semantic lexicons

Pascale Sébillot; Pierrette Bouillon; Cécile Fabre

In this paper, we propose an Inductive Logic Programming learning method which aims at automatically extracting special Noun-Verb (N-V) pairs from a corpus in order to build up semantic lexicons based on Pustejovskys Generative Lexicon (GL) principles (Pustejovsky, 1995). In one of the components of this lexical model, called the qualia structure, words are described in terms of semantic roles. For example, the telic role indicates the purpose or function of an item (cut for knife), the agentive role its creation mode (build for house), etc. The qualia structure of a noun is mainly made up of verbal associations, encoding relational information. The Inductive Logic Programming learning method that we have developed enables us to automatically extract from a corpus N-V pairs whose elements are linked by one of the semantic relations defined in the qualia structure in GL, and to distinguish them, in terms of surrounding categorial context from N-V pairs also present in sentences of the corpus but not relevant. This method has been theoretically and empirically validated, on a technical corpus. The N-V pairs that have been extracted will further be used in information retrieval applications for index expansion.


Journal of Mixed Methods Research | 2017

Integrating Multidisciplinary Results to Produce New Knowledge About the Physician–Patient Relationship A Methodology Applied to the INTERMEDE Project

Anne-Cécile Schieber; Michelle Kelly-Irving; Jean-Paul Génolini; Monique Membrado; Ludovic Tanguy; Cécile Fabre; Pascal Marchand; Thierry Lang

The INTERMEDE Project brought together a number of research teams to study the interaction between a patient and their general practitioner, and how this can produce social inequalities in health. The ultimate objective of the project was to formalize a core of common findings by integrating qualitative and quantitative results. The methodology chosen for the integration was inspired by the Delphi participatory method. It involves several rounds of questions and feedback in writing between all members of project teams, in order to compare contradictory opinions and identify key concepts arising from the project. This interdisciplinary research has provided a more nuanced understanding of the mechanisms underlying physician–patient interaction by revealing the convergences of the various disciplinary approaches.


meeting of the association for computational linguistics | 2014

Predicting the relevance of distributional semantic similarity with contextual information

Philippe Muller; Cécile Fabre; Clémentine Adam

Using distributional analysis methods to compute semantic proximity links between words has become commonplace in NLP. The resulting relations are often noisy or difficult to interpret in general. This paper focuses on the issues of evaluating a distributional resource and filtering the relations it contains, but instead of considering it in abstracto, we focus on pairs of words in context. In a discourse, we are interested in knowing if the semantic link between two items is a byproduct of textual coherence or is irrelevant. We first set up a human annotation of semantic links with or without contextual information to show the importance of the textual context in evaluating the relevance of semantic similarity, and to assess the prevalence of actual semantic relations between word tokens. We then built an experiment to automatically predict this relevance, evaluated on the reliable reference data set which was the outcome of the first annotation. We show that in-document information greatly improve the prediction made by the similarity level alone.


Cahiers de grammaire | 2000

Approche linguistique pour l'analyse syntaxique de corpus

Didier Bourigault; Cécile Fabre


Actes des 12èmes journées sur le Traitement Automatique des Langues Naturelles | 2004

Syntex, analyseur syntaxique de corpus

Didier Bourigault; Cécile Fabre; Cécile Frérot; Marie-Paule Jacques; Sylwia Ozdowska


language resources and evaluation | 2012

An empirical resource for discovering cognitive principles of discourse organisation: the ANNODIS corpus

Nicholas Asher; Farah Benamara; Myriam Bras; Cécile Fabre; Mai Ho-Dac; Anne Le Draoulec; Philippe Muller; Marie-Paule Péry-Woodley; Laurent Prévot; Josette Rebeyrolles; Ludovic Tanguy; Marianne Vergez-Couret; Laure Vieu


Archive | 2001

Linguistic clues for corpus-based acquisition of lexical dependencies

Cécile Fabre; Didier Bourigault; allées A. Machado


Journal of Machine Learning Research | 2003

Learning semantic lexicons from a part-of-speech and semantically tagged corpus using inductive logic programming

Vincent Claveau; Pascale Sébillot; Cécile Fabre; Pierrette Bouillon


Traitement Automatique des Langues Naturelles 2009 | 2008

ANNODIS: une approche outillée de l'annotation de structures discursives

Marie-Paule Péry-Woodley; Nicholas Asher; Patrice Enjalbert; Farah Benamara; Myriam Bras; Cécile Fabre; Stéphane Ferrari; Lydia-Mai Ho-Dac; A. Le Draoulec; Yann Mathet


Archive | 2002

Method and large syntactical analysis system of a corpus, a specialised corpus in particular

Didier Bourigault; Cécile Fabre

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Philippe Muller

Centre national de la recherche scientifique

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