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Many excellent results are obtained in agricultural and forestry research projects, but their practical adoption is often limited. The aim of the European project VALERIE is to increase the transfer and application of innovations produced by research in agriculture and forestry, by facilitating their integration into management practices. The project is still ongoing and the results illustrated in this paper are still temporary and subject to being improved. Here we present the methodology used in VALERIE to extract and summarise knowledge for innovation from research documents with the aim of making it available to final users through ask-Valerie.eu; we also report on current progress. The tasks associated with extracting and summarising knowledge are centred on: i) an ontology; ii) a document base; and iii) a system (ask-Valerie.eu) that allows users to effectively search the document base. An ontology defines a set of concepts and the relations between them. The VALERIE ontology is built by experts in the agricultural and forestry domain and contains 6169 concepts (21st October 2016). The document base is the collection of documents in which the system searches. The VALERIE document base includes scientific and practical documents derived from various sources, written in any of a number of languages. All documents contained in the document base are annotated using the ontology: each term (a word or a short phrase) in the document that matches a concept in the VALERIE-ontology is linked to that concept. Annotation is an automated process that takes place whenever a document is added to the document base. The document base contains 4278 documents (October 2016). Among them, there are 201 minifactsheets written by members of the VALERIE project, each describing an innovation with: a short description of the innovation, a list of correlated projects, and some links to scientific and practical documents. ask-Valerie.eu searches documents and fragments of text from the document base that address the user’s query. ask-Valerie.eu mimics the dialogue between a practitioner and an expert and achieves this functionality by: i) supporting the practitioner in articulating the question (it completes terms that the user starts to type and suggests other possibly relevant terms); ii) expanding the query using synonyms; iii) extracting and ranking text fragments from the documents.
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