Title :
Semantics-Enhanced Recommendation System for Social Healthcare
Author :
Zaman, Nazia ; Juan Li
Author_Institution :
Comput. Sci. Dept., North Dakota State Univ., Fargo, ND, USA
Abstract :
Nowadays more and more people are going online to seek for information, service and products to address their health concerns. Given the mountains of online health-related data, it is time and energy consuming for people to locate the right information directly related to their health concerns. Therefore, effective recommendation is very important to save people´s time and energy by providing them with the appropriate information. In this paper, we propose a recommendation system which utilizes semantic web technology and healthcare social networking to provide personalized recommendation to speed patient recovery and improve healthcare outcomes. Extensive experiments have been performed to evaluate the performance of the system. The results demonstrated the effectiveness of the proposed strategy.
Keywords :
health care; medical information systems; recommender systems; semantic Web; social networking (online); healthcare social networking; online health-related data; patient recovery; personalized recommendation; semantic Web technology; semantics-enhanced recommendation system; Collaboration; Information filtering; Medical services; Ontologies; Semantics; Social network services; healthcare; recommendation; semantics; social network;
Conference_Titel :
Advanced Information Networking and Applications (AINA), 2014 IEEE 28th International Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
978-1-4799-3629-8
DOI :
10.1109/AINA.2014.93