Collaborative Group Decision for knowledge acquisition in agriculture using AI techniques

Project Abstract

Knowledge acquisition is a key step to understand the domain in order to make proposals to obtain better results. Natural Language Processing tools in combination with Machine Learning (both from the Artificial Intelligence field) can be used to analyze the narrative descriptions captured, in order to obtain an ontology representation of the knowledge acquired. Considering the agricultural context and the use of technology, knowledge acquisition should be done with tools that suit the characteristics of the stakeholders and provide the accuracy of knowledge description needed in a technological environment. We consider three aspects to be taken into account. Collaborative Knowledge Management (CKM) is considered as a process of collective resolution of problems where it is useful to memorize the process of making collective decisions and to structure the group interactions to facilitate problem solving and sharing of ideas. Then scenarios are widely used to capture the knowledge from the stakeholders. Finally, conflict resolution is a step to be considered in knowledge acquisition. It is crucial making the group decision process interactive, iterative, collaborative and participatory. Thus, a multi-criteria decision support system arises as a tool to support this process.