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24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

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Scientific documents annotation with @Web


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A new data paper about Milling itineraries dataset for a collection of crop and wood by-products and granulometric properties of the resulting powders

A new data paper about Milling itineraries dataset for a collection of crop and wood by-products (
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A new data paper about consumer perception data and scientific arguments about food packaging functionalities for fresh strawberries

This data article contains data characterizing consumer perception and scientific arguments about food packaging functionalities for fresh...
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Evagrain ANR project (2021-2024)

The ambition of EVAGRAIN is to design a Decision Support System (DSS) that will compute a general assessment of the wheat quality for various...
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A new paper accepted in Wims'2020: SciPuRe: a new Representation of textual data for entity identification from scientific publications

content of scientific documents faces numbers of challenges. One of them is the assessment of the extracted entities for further process, especially...
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D2KAB ANR project (2019-2022)

D2KAB ANR project creates a framework to turn agronomy and biodiversity data into knowledge –semantically described, interoperable, actionable,...
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New publication: Xart: Discovery of correlated arguments of n-ary relations in text

Here we present the Xart system based on a three-step hybrid method using data mining approaches and syntactic analysis to automatically discover and...
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@Web, a software to annotate heterogeneous scientific data sources guided by a termino-ontological resource

@Web is a semantic web application using a predefined vocabulary (called ontology in the following) organized as a taxonomy. @Web is a semi-automatic tool designed to help domain experts to annotate data found in scientific documents (publications, data sheets, ...). @Web project is a joint collaboration between UMR INRA MIA AgroParisTech/INRA, UMR INRA IATE, INRIA GraphiK, UMR CNRS Heudyasic, UMR INRA Mistea and Plastic platform (INRA CEPIA software platform).

We focus on data tables as they often contain a synthesis of experimental results published in scientific publications. The user downloads an HTML scientific document, then data tables are semi-automatically identified and extracted from the document. A graphical user-friendly interface helps the user to annotate data tables thanks to the ontology. Annotators may suggest evolutions of the ontology (new candidate terms of the vocabulary) which are managed by the ontology administrator. Metadata are associated with documents in order to assess documents’ reliability. Relevant annotated information from scientific data tables may be queried thank to a semantic browser using the ontology.