What does DeciTrustNET stands for?
DeciTrustNET main objective is to develop a Trust based Decision Support System for Social Networks with Uncertain Knowledge.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 746398
What are we doing?
In real world decision-making, such as public security, social choice or recommender systems, we have a large body of data from various networked heterogeneous information sources or individuals that often conflict with each other and provide inconsistent knowledge. It is a challenging task to yield an optimal consensus decision, given the range of individual decisions obtained in terms of these knowledge sources.
This research proposal aims to create a novel mathematical and computational framework for trust based social choice in networks and with uncertain knowledge by merging multiple individuals’ preferences in an adaptive manner to reduce the disagreements among them, and automatically seek a decision or provide a recommendation with a maximal consensus.
To achieve our goal, we propose to bring together, for the first time, four previously disparate strands of research: social network analysis, fuzzy preference modelling, multiple attribute group decision-making and game theoretic modelling of malicious users.
As a showcase the proposed framework will be used to develop a e-health social network based on trust to increase the healthy lifestyle in patients with specific needs.
What are the possible applications?
The research outcomes will be adaptable to use in situations that requires reactive, adaptive online decision-making.
New possible policies could be posted in SNs and social reaction be analysed for governments to offer more effective services to the society they represent.
It could also be used to engage youth in e-democracy.
The proposed e-health application provides an innovative tool that is directly linked to the H2020 Health, Demographic Change and Wellbeing challenge, which could cut expenses in social security and health care. This impact will be manifest as a quality of life enhancement.
Who is taking part?
The main project coordinators are:
- PhD. M.R. Ureña , Marie Curie IF , Centre For Computational Intelligence, De Montfort University, Leicester
- Prof. F. Chiclana, Professor in the Centre For Computational Intelligence, De Montfort University, Leicester