User recommendation in healthcare social media by assessing user similarity in heterogeneous network.
Journal:
Artificial intelligence in medicine
Published Date:
Sep 1, 2017
Abstract
OBJECTIVE: The rapid growth of online health social websites has captured a vast amount of healthcare information and made the information easy to access for health consumers. E-patients often use these social websites for informational and emotional support. However, health consumers could be easily overwhelmed by the overloaded information. Healthcare information searching can be very difficult for consumers, not to mention most of them are not skilled information searcher. In this work, we investigate the approaches for measuring user similarity in online health social websites. By recommending similar users to consumers, we can help them to seek informational and emotional support in a more efficient way.