Multi-Level Health Knowledge Mining Process in P2P Edge Network

Chronic diseases are increasing due to westernized eating habits and everyday life changes, healthcare disease prevention should be managed based on constant interest. Users, who not health professionals, have difficulty in obtaining accurate information related noise problems such as subjective opinions, distorted information, exaggerated information. There is a need for method that enables users obtain meaningful real-time among the vast amounts of data collected through search. In this study, we propose multi-level knowledge mining process P2P edge network. The proposed suggests network solve overload problem networking, problem, security cloud computing mines mutual according association rules. addition, results visualized by which can easily receive relevant As result performance evaluation, F-measure using recall precision 83%, 79%, 75%, 74%, 73% support ratings 10%, 20%, 30%, 40%, 50% Was derived. Accordingly, it possible analyze healthcare-related tree computing. visualizing user embedding structure, provides personalized intuitive understanding.