Mining the gaps: Using machine learning to map 1.2 million agri-food publications from the Global South



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https://tapipedia.org/sites/default/files/p4336_cosai_brief_3_mapping_study_v3.pdf
Sujet(s): 
Licence de la ressource: 
Droits soumis à la permission du propriétaire
Type: 
note d'orientation
Auteur: 
Commission on Sustainable Agriculture Intensification (CoSAI)
Description: 

The evidence base on agri-food systems is growing exponentially. The CoSAI-commissioned study, Mining the Gaps, applied artificial intelligence to mine more than 1.2 million publications for data, creating a clearer picture of what research has been conducted on small-scale farming and post-production systems from 2000 to the present, and where evidence gaps exist.

The study used Havos AI machine learning models to extract information from each publication based on a series of modular questions. Graphical maps of the data provide policymakers and funders with a more nuanced view of the information available, which can help them to prioritize and coordinate international funding and research efforts.

Αnnée de publication: 
2021
Μots-clés: 
Global South
agricultural data
agricultural research
Machine learning