Open Data Platform for Knowledge Access in Plant Health Domain : VESPA Mining
This work addresses the challenge of accessing locked agricultural data for plant health management, though it appears incremental compared to prior attempts.
The paper tackles the problem of extracting pest-crop interaction data from historical literature by developing VESPA, a text mining platform that models and predicts crop attacks to reduce pesticide use, achieving a novel parsing approach based on document architecture.
Important data are locked in ancient literature. It would be uneconomic to produce these data again and today or to extract them without the help of text mining technologies. Vespa is a text mining project whose aim is to extract data on pest and crops interactions, to model and predict attacks on crops, and to reduce the use of pesticides. A few attempts proposed an agricultural information access. Another originality of our work is to parse documents with a dependency of the document architecture.