Personalized Healthcare Recommender Based on Social Media

Abstract

Social media is rapidly changing the nature and speed of healthcare interaction. As more and more people go online to search for their health-related issues, providing them with appropriate information would save them from being overwhelmed by mountains of information. For this purpose, in this paper we propose a personalized healthcare recommending system to recommend highly relevant and trustworthy healthcare-related information to users. The system identifies key factors impacting the recommendation in a healthcare social networking environment, and uses semantic web technology and fuzzy logic to represent and evaluate the recommendation. Experiments were conducted and demonstrated that our approach can generate good outcomes in making recommendation and predicting the scope and impact of different factors.