A Fuzzy Modeling Approach for Group Decision Making in Social Networks

Abstract

Social networks have been commonly used, people use social networks with various purposes, such as, enjoying time, making business, and contacting their friends. All these activities are mainly based on sharing data. In social networks, making decision on data sharing process has become one of the main challenge because it involves people who have different opinions on the same problem. Diversified opinions cause uncertainties in decision making process. Fuzzy logic is used to overcome uncertainties' situations. In this work, we provide a fuzzy logic based decision making framework for SNs. The proposed fuzzy logic based framework uses data sensitivity value and trust value (confidence value) to make the group decision. Users express their opinions on data security features to obtain aggregated decision. Facebook data sharing process is chosen as a case study.

Analysis and Design of the Health Management System for Medical Staffs

“…In (2), SS refers to the social support which is classified into the following 5 levels: very bad, bad, fair, good, very good, while WL stands for workload.…”

“…With the fast-paced development of such novel technologies as big data, Internet of Things and artificial intelligence, there have been an increasing number of scholars interested in exploring how to build the health management system dedicated to health management and disease prevention [1]. Based on the big data technology, the health management system can store and analyse the data collected from different resources including public health, clinical treatment and medical research [2]. The intelligent operating analysis of these data is especially helpful in improving the performance in decision support-based public health, clinical treatment and medical research in the future, thus leading to a virtuous circle [3].…”