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Fuzzy Consensus Model in Collective Knowledge Systems: An Application for Fighting Food Frauds

机译:集体知识系统中的模糊共识模型:对食物欺诈的应用

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Food fraud is related to different illicit conducts which aim at gaining economic benefit from counterfeiting food and ignoring the damage they cause to public economy and health. Consumers use the new technologies, like social networks, in order to share their worries about food frauds and to stay informed about them. But, in such a complex and dynamic context, it is important to ensure the reliability of news about food frauds in order to avoid misinformation and general panic phenomena. In this context, we propose an extension of a Collective Knowledge System aiming at verifying the reliability of news about food frauds and to decide whether to publish and spread information on the food frauds in the society. A Fuzzy Consensus Model has been proposed for helping the experts in achieving a shared decision about the reliability of each news and about its publication and diffusion. An illustrative example demonstrates the feasibility and the usefulness of the proposed approach.
机译:食品欺诈与不同的非法行为有关,旨在获得经济效益,从伪造食物中取消,忽略他们对公共经济和健康的损害。消费者使用新技术,如社交网络,以分享他们对食物欺诈的担忧,并留下通知他们。但是,在这种复杂和动态的背景下,重要的是要确保有关食物欺诈的新闻的可靠性,以避免错误信息和普通恐慌现象。在这方面,我们提出了一个集体知识系统的延伸,旨在验证有关食物欺诈的新闻的可靠性,并决定是否公布和传播关于社会的食物欺诈信息。已经提出了一种模糊共识模型,帮助专家在实现每个新闻的可靠性以及其出版物和扩散的可靠性方面实现共同决定。说明性示例展示了所提出的方法的可行性和有用性。

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