Text Mining and Agriculture: The AgroNLP projects

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The TETIS team (Territoires, Environnement, Télédetection et Information Spatiale or Land, environment, remote sensing and spatial information in English) is a Joint Research Unit of some of the major French actors in text mining and Natural Language Processing, namely AgroParisTech, Irstea (National Research Institute of Science and Technology for Environment and Agriculture) and Cirad (the International Cooperation Centre for Agricultural Development Research). It is located in Montpellier. The TETIS Unit has been really active in projects related to the application of text mining in use cases in the agricultural sector.

These AgroNLP projects (Natural Language Processing applied to AGRicultural dOmain) aim to address different challenges faced by stakeholders in the agri-food sector, such as:

  • Animal Disease Surveillance: The project proposes a new methodology in the domain of epidemic intelligence in animal health in order to discover knowledge in web documents dealing with animal disease outbreaks. To address this issue, a global process based on Information Retrieval (IR) and Information Extraction (IE) approaches is proposed. This is working on the same direction as our Foodakai project.

Source: http://www.textmining.biz/agroNLP.html

  • Terminology Extraction for Document Matching and Open Data in Agricultural Domain: The project investigates the use and combination of Text Mining methodologies to highlight and publish in Open Data systems the most appropriate terms extracted with BioTex (both in French and in English). In addition, these terms are used to match heterogeneous data of agricultural domain.
  • Information Extraction from Experimental Data of Agricultural Domain: This work seems to be the most technical of all, as it deals with knowledge engineering issues of experimental data that are extracted from scientific articles, in order for them to be reused in decision support systems. The work is based on Natural Language Processing (NLP) together with data mining approaches guided by the domain Ontological and Terminological Resource (OTR).
  • BIg Data for Agriculture and biodiversitY (BIRTHDAY): This project aims at providing new efficient decision making tools for helping agricultural development as well as biodiversity protection in Peru. More specifically, it aims at developing a new platform for helping to acquire new data, to share data, to extract knowledge, and to share useful information and knowledge among different actors that are involved in agriculture or biodiversity domains in Peru. We were happy to see Sophia Ananiadou from the University of Manchester/NACTEM Director (also an OpenMinTeD consortium member) among the researchers working on this project.

You can find more information about these projects on the TETIS Unit website.

Through our participation in the OpenMinTeD project, we aim to explore and identify additional applications of text mining on agri-food research publications, as well as to provide insight on the existing work at a global level.

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