RHECITAS: citation analysis of French humanities articles

International audienceThe RHECITAS project aims at the analysis of citations in French Humanities and Social Sciences articles using natural language processing techniques. It is based on a corpus of online articles, through the aid of natural language processing tools. The project is funded by TGE-ADONIS (CNRS, French National Research Centre). Although very little research, either theoretical and technical, has been made on such data (most approaches focusing on science publications written in English), we developed two different tools that can automatically a) identify the more important items in a list of references, based on a number of linguistic cues, and b) extract relevant terms associated to a reference. These results show a new angle on citation analysis, both from a linguistic point of view and for practical applications

Un mod{\`e}le de base de connaissances terminologiques

In the present paper, we argue that Terminological Knowledge Bases (TKB) are all the more useful for addressing various needs as they do not fulfill formal criteria. Moreover, they intend to clarify the terminology of a given domain by illustrating term uses in various contexts. Thus we designed a TKB structure including 3 linked features: terms, concepts and texts, that present the peculiar use of each term in the domain. Note that concepts are represented into frames whose non-formal description is standardized. Associated with this structure, we defined modeling criteria at the conceptual level. Finaly, we discuss the situation of TKB with regard to ontologies, and the use of TKB for the development of AI systems.Comment: in French language. 2{\`e}mes Rencontres Terminologie et Intelligence Artificielle (TIA 1997), Groupe de recherche TIA : Terminologie et intelligence artificielle, UT2 LeMirail, Toulouse, Apr 1997, Toulouse, Franc

Un modèle de base de connaissances terminologiques

International audienceIn the present paper, we argue that Terminological Knowledge Bases (TKB) are all the more useful for addressing various needs as they do not fulfill formal criteria. Moreover, they intend to clarify the terminology of a given domain by illustrating term uses in various contexts. Thus we designed a TKB structure including 3 linked features: terms, concepts and texts, that present the peculiar use of each term in the domain. Note that concepts are represented into frames whose non-formal description is standardized. Associated with this structure, we defined modeling criteria at the conceptual level. Finaly, we discuss the situation of TKB with regard to ontologies, and the use of TKB for the development of AI systems.Dans cet article, nous défendons l'hypothèse que les Bases de Connaissances Terminologiques (BCT) sont d'autant plus utiles pour des utilisations différentes qu'elles ne sont pas formelles, et qu'elles se limitent au rôle de clarifier la terminologie d'un domaine en illustrant son utilisation en contexte. Nous avons mis au point un modèle de structuration de BCT afin qu’elles répondent à cet objectif. Ce modèle définit trois types d'entités reliées entre elles : termes, concepts et textes. Il rend également compte des particularités d’usage des termes. Les concepts sont représentés à l’aide de frames dont la description, non formelle, est normalisée. Associés à ce modèle, nous avons fixé des critères de modélisation des concepts. Nous montrons comment ces propositions contribuent au débat sur la situation des BCT par rapport aux ontologies et leur utilisation pour le développement d'applications en IA

Extraction de relations sémantiques entre termes et enrichissement de modèles conceptuel

International audienc

Cross Lingual Question Answering using QRISTAL for CLEF 2005

QRISTAL [8] is a question answering system making intensive use of natural language processing both for indexing documents and extracting answers. It recently ranked first in the EQueR evaluation campaign (Evalda, Technolangue [3]). This article proposes a functional description of the system. Then, it presents our results for the CLEF 2005 campaign and a critical description of the system. QRISTAL is possibly the first Question Answering system available on the consumer market. That fact generates drastic constraints and explains the technical choices we detail here.

Nicotine receptors in the mammalian brain

Nicotine is a drug of abuse that presumably exerts its psychoactive effect through its interactions with nicotine binding sites in the central nervous system. Among its potential sites of action are the neuronal nicotinic acetylcholine receptors and the neuronal α‐bungarotoxin binding sites. In this review we focus on the neuronal nicotinic acetylcholine receptors, their diversity, distribution, and functions as nicotine receptors or as mediators of synaptic transmission in the mammalian brain. We find that the complexity characteristic of the gene family encoding the subunits of these receptors is reflected both in the pattern of expression of the genes and in the pharmacological diversity of the expressed receptors.—Luetje, C. W.; Patrick, J.; Séguéla, P. Nicotine receptors in the mammalian brain. FASEB J. 4: 2753‐2760; 1990

L’apprentissage d’ordonnancement pour l’appariement de questions

National audienceCet article présente une approche permettant à un utilisateur d’interroger une base de connaissances type FAQ, c’est-à-dire un ensemble de questions et leurs réponses respectives rédigées en langue naturelle. Le composant présenté dans cet article apparie la question de l’utilisateur à une ou plusieurs questions de la base de connaissances. Pour cela, nous utilisons un composant déjà existant d’analyse de questions, capable de sélectionner un ensemble de questions candidates proches de la question utilisateur, et de produire des traits propres à chaque couple (question utilisateur, question candidate). Ce composant est chaîné à un modèle permettant l’ordonnancement des questions candidates, qui est appris automatiquement de façon supervisée, une partie seulement du corpus d'apprentissage étant annotée manuellement, et le reste grâce à des règles add-hoc. Ces travaux reprennent les résultats d’un domaine de recherche récent, l’apprentissage d’ordonnancement (Learning to Rank), et les adaptent à une application industrielle innovante, l’appariement de questions comme paradigme d’accès à la connaissance. Une expérimentation évalue sur des données issues d’un système en production la qualité de chacune des phases d’apprentissage

Chronic lithium treatment alters the excitatory/inhibitory balance of synaptic networks and reduces mGluR5–PKC signalling in mouse cortical neurons

International audienceBackground: Bipolar disorder is characterized by cyclical alternation between mania and depression, often comorbid with psychosis and suicide. Compared with other medications, the mood stabilizer lithium is the most effective treatment for the prevention of manic and depressive episodes. However, the pathophysiology of bipolar disorder and lithium’s mode of action are yet to be fully understood. Evidence suggests a change in the balance of excitatory and inhibitory activity, favouring excitation in bipolar disorder. In the present study, we sought to establish a holistic understanding of the neuronal consequences of lithium exposure in mouse cortical neurons, and to identify underlying mechanisms of action.Methods: We used a range of technical approaches to determine the effects of acute and chronic lithium treatment on mature mouse cortical neurons. We combined RNA screening and biochemical and electrophysiological approaches with confocal immunofluorescence and live-cell calcium imaging.Results: We found that only chronic lithium treatment significantly reduced intracellular calcium flux, specifically by activating metabotropic glutamatergic receptor 5. This was associated with altered phosphorylation of protein kinase C and glycogen synthase kinase 3, reduced neuronal excitability and several alterations to synapse function. Consequently, lithium treatment shifts the excitatory–inhibitory balance toward inhibition.Limitations: The mechanisms we identified should be validated in future by similar experiments in whole animals and human neurons.Conclusion: Together, the results revealed how lithium dampens neuronal excitability and the activity of the glutamatergic network, both of which are predicted to be overactive in the manic phase of bipolar disorder. Our working model of lithium action enables the development of targeted strategies to restore the balance of overactive networks, mimicking the therapeutic benefits of lithium but with reduced toxicity