Laura Monceaux


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DEFT2018 : recherche d’information et analyse de sentiments dans des tweets concernant les transports en Île de France (DEFT2018 : Information Retrieval and Sentiment Analysis in Tweets about Public Transportation in Île de France Region )
Patrick Paroubek | Cyril Grouin | Patrice Bellot | Vincent Claveau | Iris Eshkol-Taravella | Amel Fraisse | Agata Jackiewicz | Jihen Karoui | Laura Monceaux | Juan-Manuel Torres-Moreno
Actes de la Conférence TALN. Volume 2 - Démonstrations, articles des Rencontres Jeunes Chercheurs, ateliers DeFT

Cet article présente l’édition 2018 de la campagne d’évaluation DEFT (Défi Fouille de Textes). A partir d’un corpus de tweets, quatre tâches ont été proposées : identifier les tweets sur la thématique des transports, puis parmi ces derniers, identifier la polarité (négatif, neutre, positif, mixte), identifier les marqueurs de sentiment et la cible, et enfin, annoter complètement chaque tweet en source et cible des sentiments exprimés. Douze équipes ont participé, majoritairement sur les deux premières tâches. Sur l’identification de la thématique des transports, la micro F-mesure varie de 0,827 à 0,908. Sur l’identification de la polarité globale, la micro F-mesure varie de 0,381 à 0,823.


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Evaluating Lexical Similarity to build Sentiment Similarity
Grégoire Jadi | Vincent Claveau | Béatrice Daille | Laura Monceaux
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

In this article, we propose to evaluate the lexical similarity information provided by word representations against several opinion resources using traditional Information Retrieval tools. Word representation have been used to build and to extend opinion resources such as lexicon, and ontology and their performance have been evaluated on sentiment analysis tasks. We question this method by measuring the correlation between the sentiment proximity provided by opinion resources and the semantic similarity provided by word representations using different correlation coefficients. We also compare the neighbors found in word representations and list of similar opinion words. Our results show that the proximity of words in state-of-the-art word representations is not very effective to build sentiment similarity.

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Extraction d’expressions-cibles de l’opinion : de l’anglais au français (Opinion Target Expression extraction : from English to French)
Grégoire Jadi | Laura Monceaux | Vincent Claveau | Béatrice Daille
Actes de la conférence conjointe JEP-TALN-RECITAL 2016. volume 2 : TALN (Posters)

Dans cet article, nous présentons le développement d’un système d’extraction d’expressions-cibles pour l’anglais et sa transposition au français. En complément, nous avons réalisé une étude de l’efficacité des traits en anglais et en français qui tend à montrer qu’il est possible de réaliser un système d’extraction d’expressions-cibles indépendant du domaine. Pour finir, nous proposons une analyse comparative des erreurs commises par nos systèmes en anglais et français et envisageons différentes solutions à ces problèmes.


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Learning Subjectivity Phrases missing from Resources through a Large Set of Semantic Tests
Matthieu Vernier | Laura Monceaux | Béatrice Daille
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

In recent years, blogs and social networks have particularly boosted interests for opinion mining research. In order to satisfy real-scale applicative needs, a main task is to create or to enhance lexical and semantic resources on evaluative language. Classical resources of the area are mostly built for english, they contain simple opinion word markers and are far to cover the lexical richness of this linguistic phenomenon. In particular, infrequent subjective words, idiomatic expressions, and cultural stereotypes are missing from resources. We propose a new method, applied on french, to enhance automatically an opinion word lexicon. This learning method relies on linguistic uses of internet users and on semantic tests to infer the degree of subjectivity of many new adjectives, nouns, verbs, noun phrases, verbal phrases which are usually forgotten by other resources. The final appraisal lexicon contains 3,456 entries. We evaluate the lexicon enhancement with and without textual context.


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FRASQUES: A Question Answering system in the EQueR evaluation campaign
Brigitte Grau | Anne-Laure Ligozat | Isabelle Robba | Anne Vilnat | Laura Monceaux
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

Question-answering (QA) systems aim at providing either a small passage or just the answer to a question in natural language. We have developed several QA systems that work on both English and French. This way, we are able to provide answers to questions given in both languages by searching documents in both languages also. In this article, we present our French monolingual system FRASQUES which participated in the EQueR evaluation campaign of QA systems for French in 2004. First, the QA architecture common to our systems is shown. Then, for every step of the QA process, we consider which steps are language-independent, and for those that are language-dependent, the tools or processes that need to be adapted to switch for one language to another. Finally, our results at EQueR are given and commented; an error analysis is conducted, and the kind of knowledge needed to answer a question is studied.


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The Ongoing Evaluation Campaign of Syntactic Parsing of French: EASY
Anne Vilnat | Patrick Paroubek | Laura Monceaux | Isabelle Robba | Véronique Gendner | Gabriel Illouz | Michèle Jardino
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

This paper presents EASY (Evaluation of Analyzers of SYntax), an ongoing evaluation campaign of syntactic parsing of French, a subproject of EVALDA in the French TECHNOLANGUE program. After presenting the elaboration of the annotation formalism, we describe the corpus building steps, the annotation tools, the evaluation measures and finally, plans to produce a validated large linguistic resource, syntactically annotated


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PEAS, the first instantiation of a comparative framework for evaluating parsers of French
Véronique Gendner | Gabriel Illouz | Michèle Jardino | Laura Monceaux | Patrick Paroubek | Isabelle Robba | Anne Vilnat
10th Conference of the European Chapter of the Association for Computational Linguistics


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Cooperation between black box and glass box approaches for the evaluation of a question answering system
Martine Hurault-Plantet | Laura Monceaux
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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A Protocol for Evaluating Analyzers of Syntax (PEAS)
Véronique Gendner | Gabriel Illouz | Michèle Jardino | Laura Monceaux | Patrick Paroubek | Isabelle Robba | Anne Vilnat
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)