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
Supporting multi-criteria decisions based on a hierarchical structure by taking advantage of acquired knowledge
In this paper, an approach to decision making is described. It combines a knowledge acquisition technique, a multi-attribute decision making technique, a validation technique and a machine learning algorithm. The suggested system is an extension of a previous decision_support system based on the fuzzy repertory table technique. The aim is to increase its efficiency when dealing with a great amount of alternatives and criteria. The solution is based on a mechanism to divide the original problem into several simpler sub-problems. Moreover, a case study is presented to illustrate how the proposed system is used to design a Product Search Assistant. It will be integrated into a multi-agent architecture developed to give support to an e-marketplace. (C) 2012 Elsevier B. V. All rights reserved.
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