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- W2471760937 abstract "Large amounts of textual data related to the agriculture domain are now available. Knowledge discovery becomes a crucial issue for research organizations, decision makers, and users. Our work investigates the use of emph{Text Mining} methodologies in order to tackle several issues such as Animal Disease Surveillance, Open Data in Agriculture Domain, Information Extraction from Experimental Data. In this context, we have defined a new Knowledge Discovery from Texts (KDT) process applied to the agriculture domain (http://textmining.biz/agroNLP.html). This one is divided into four steps: (i) data acquisition, (ii) information retrieval, (iii) information extraction and disambiguation, (iv) visualization and evaluation. In this KDT process applied to specific use-cases, the integration of expert knowledge has a key role." @default.
- W2471760937 created "2016-07-22" @default.
- W2471760937 creator A5014118555 @default.
- W2471760937 date "2016-05-07" @default.
- W2471760937 modified "2023-09-23" @default.
- W2471760937 title "Knowledge discovery from texts on agriculture domain" @default.
- W2471760937 hasPublicationYear "2016" @default.
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