A survey of the applications of text mining for agriculture
2019
Drury, Brett | Roche, Mathieu | Institute for Systems and Computer Engineering, Technology and Science [Porto] (INESC TEC) | Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS) | Département Environnements et Sociétés (Cirad-ES) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) | Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) - 16/15524-3
International audience
显示更多 [+] 显示较少 [-]英语. Agricultural researchers, in common with other domains, have recently began to have access to large collections of agricultural texts such as scientific papers and news stories. These texts can be analysed with text mining techniques to resolve agricultural problems or extract knowledge. Despite the potential of these techniques, text mining is a relatively underused technique in the agricultural domain. Therefore, this survey is intended to provide a current state of the art survey of the application of text mining techniques to agricultural problems.
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