Maladie coeliaque associée à une maladie de Basedow et un déficit sélectif en IgA chez une fille de 4 ans

La maladie coeliaque est une entéropathie auto-immune, induite par l'ingestion du gluten chez des sujets génétiquement prédisposés. Son association à d'autres maladies auto-immunes est décrite. Néanmoins l'association de la maladie céliaque, la maladie de Basedow et le déficit en IgA sélectif est rarement relevée chez l'enfant. Nous rapportons l'observation exceptionnelle d'une fille âgée de 4 ans qui présente une maladie c'liaque associée à une maladie de basedow et un déficit sélectif en IgA.Pan African Medical Journal 2015; 2

Type Theories and Lexical Networks: using Serious Games as the basis for Multi-Sorted Typed Systems

In this paper, we show how a rich lexico-semantic network which has been built using serious games, JeuxDeMots, can help us in grounding our semantic ontologies as well as different sorts of information in doing formal semantics using rich or modern type theories (type theories within the tradition of Martin Löf). We discuss the domain of base types, adjectival and verbal types, hyperonymy/hyponymy relations as well as more advanced issues like homophony and polysemy. We show how one can take advantage of this wealth in a formal compositional semantics framework. This is a way to sidestep the problem of deciding how your type ontology should look like once you have made a move to a many sorted type system. Furthermore, we show how this kind of information can be extracted  from JeuxdeMots and inserted into a proof-assistant like Coq in order to perform reasoning tasks using modern type theoretic semantics

The SSIX Corpora: Three Gold Standard Corpora for Sentiment Analysis in English, Spanish and German Financial Microblogs

This paper introduces the three SSIX corpora for sentiment analysis. These corpora address the need to provide annotated data for supervised learning methods. They focus on stock-market related messages extracted from two financial microblog platforms, i.e., StockTwits and Twitter. In total they include 2,886 messages with opinion targets. These messages are provided with polarity annotation set on a continuous scale by three or four experts in each language. The annotation information identifies the targets with a sentiment score. The annotation process includes manual annotation verified and consolidated by financial experts. The creation of the annotated corpora took into account principled sampling strategies as well as inter-annotator agreement before consolidation in order to maximize data quality

The SSIX Corpora: Three Gold Standard Corpora for Sentiment Analysis in English, Spanish and German Financial Microblogs

This paper introduces the three SSIX corpora for sentiment analysis. These corpora address the need to provide annotated data for supervised learning methods. They focus on stock-market related messages extracted from two financial microblog platforms, i.e., StockTwits and Twitter. In total they include 2,886 messages with opinion targets. These messages are provided with polarity annotation set on a continuous scale by three or four experts in each language. The annotation information identifies the targets with a sentiment score. The annotation process includes manual annotation verified and consolidated by financial experts. The creation of the annotated corpora took into account principled sampling strategies as well as inter-annotator agreement before consolidation in order to maximize data quality

SemR-11: A Multi-Lingual Gold-Standard for Semantic Similarity and Relatedness for Eleven Languages

This work describes SemR-11, a multi-lingual dataset for evaluating semantic similarity and relatedness for 11 languages (German, French, Russian, Italian, Dutch, Chinese, Portuguese, Swedish, Spanish, Arabic and Persian). Semantic similarity and relatedness gold standards have been initially used to support the evaluation of semantic distance measures in the context of linguistic and knowledge resources and distributional semantic models. SemR-11 builds upon the English gold-standards of Miller & Charles (MC), Rubenstein & Goodenough (RG), WordSimilarity 353 (WS-353), and Simlex-999, providing a canonical translation for them. The final dataset consists of 15,917 word pairs and can be used to support the construction and evaluation of semantic similarity/relatedness and distributional semantic models. As a case study, the SemR-11 test collections was used to investigate how different distributional semantic models built from corpora in different languages and with different sizes perform in computing semantic relatedness similarity and relatedness tasks

Implicit and Explicit Aspect Extraction in Financial Microblogs

This paper focuses on aspect extraction which is a sub-task of Aspect-based Sentiment Analysis. The goal is to report an extraction method of financial aspects in microblog messages. Our approach uses a stock-investment taxonomy for the identification of explicit and implicit aspects. We compare supervised and unsupervised methods to assign predefined categories at message level. Results on 7 aspect classes show 0.71 accuracy, while the 32 class classification gives 0.82 accuracy for messages containing explicit aspects and 0.35 for implicit aspects

Implicit and Explicit Aspect Extraction in Financial Microblogs

This paper focuses on aspect extraction which is a sub-task of Aspect-based Sentiment Analysis. The goal is to report an extraction method of financial aspects in microblog messages. Our approach uses a stock-investment taxonomy for the identification of explicit and implicit aspects. We compare supervised and unsupervised methods to assign predefined categories at message level. Results on 7 aspect classes show 0.71 accuracy, while the 32 class classification gives 0.82 accuracy for messages containing explicit aspects and 0.35 for implicit aspects

Nile Tilapia “Oreochromis niloticus” Farming in Fresh and Geothermal Waters in Tunisia: A Comparative Study

This work aims to compare the farming of Nile Tilapia Oreochromis niloticus in fresh and geothermal waters through monitoring the specie’s zootechnical parameters: growth, mortality and feed conversion rate. For geothermal water rearing, fish was placed in cages in Bechima Station, in southern Tunisia, while Smati Reservoir, in the center of the country was used for fresh water. The spawners were first adapted to geothermal waters in Bechima experimental station. Then, the broodstock phase lasted 60 days and allowed the obtainment of 1–2 g larvae. Fertility was important and varied between 451 and 1589 larvae/female, which is associated with the females’ total weight (F = 1.6 W2.1). In the pre-growing phase, the comparison of fry growth rates (weight 1.3 g) in the geothermal and freshwaters showed a small variation with recorded rates slightly in favor of fish bred in fresh water. During 50 days within the breeding phase, fish weight achieved in freshwater was more important reaching 12.7 g (TCJ = 0.228 g /day compared to 10.51 g (TCJ = 0.184 g/day) recorded in geothermal waters. Similarly, during the fattening phase, the weights gained after 30days demonstrated better growth rates for tilapia cultured in freshwater (up to 60 g) in contrast to that bred in geothermal water (35–40 g)

Consolidation endogène de réseaux lexico-sémantiques : Inférence et annotation de relations, règles d'inférence et langage dédié

Developing lexico-semantic resources is a major issue in the Natural Language Processing field.These resources, by making explicit inter alia some knowledge possessed only by humans, aim at providing the ability of a precise and complete text understanding to NLP tasks. Popular resources-building strategies involving crowdsourcing are flowering in NLP and are proved to be successful. However, the resulted resources are not free of errors and lack some important semantic relations. In this PhD thesis, we used the french lexico-semantic network from the project JeuxDeMots as a case-study. We designed an endogenous consolidation system for this type of networks based on inferring and annotating new semantic relations using the already existing ones, as well as extracting and proposing inference rules able to (re)generate a considerable part of the network. In addition, we conceived a domain specific language for manipulating the consolidation system along with the network itself and a prototype was implemented.Développer des ressources lexico-sémantiques pour le Traitement Automatique des Langues Naturelles est un enjeu majeur du domaine. Ces ressources explicitant notamment des connaissances que seuls les humains possèdent, ont pour but de permettre aux applications de TALNune compréhension de texte assez fine et complète. De nouvelles approches populaires de construction de ces dernières impliquant l'externalisation ouverte (crowdsourcing) émergent en TALN. Elles ont confirmé leur efficacité et leur pertinence. Cependant, les ressources obtenues ne sont pas exemptes d'informations erronées ou de silences causés par l'absence de certaines relations sémantiques pertinentes et primordiales pour la bonne qualité. Dans ce travail de recherche, nous prenons comme exemple d'étude le réseau lexico-sémantique du projet JeuxDeMots et nous proposons un système de consolidation endogène pour ce type de réseaux.Ce système se base principalement sur l'enrichissement du réseau par l'inférence et l'annotation de nouvelles relations à partir de celles existantes, ainsi que l'extraction de règles d'inférence permettant de (re)générer une grande partie du réseau. Enfin, un langage dédié de manipulation du système de consolidation et du réseau lexico-sémantique est conçu et un premier prototype a été implémenté