The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
A text segmentation method of Text to Speech Technology based on agricultural ontology theory and semantic search
This paper designed a text segmentation method of Text to Speech Technology (TTS) based on agricultural ontology theory and semantic search, which is focused on the provision of agricultural knowledge for farmers in China through call centre. This method incorporated the module of semantic search based on agricultural ontology to process ambiguous phrase, this incorporation is made without any alteration of semantic search module, and not to search anything through ambiguous phrase (key word). Ontology design methodology and semantic inference model based on ontology do not need to be altered neither, but only extending some ontology examples according to concrete agricultural knowledge. This method could reduce the cost of call centre, and also provide an effective channel of agricultural knowledge providing for Chinese farmers.
Inappropriate format for Document type, expected simple value but got array, please use list format