Internet has overabundance of health information that is frequently misleading. Recent studies show that patients look for quality health information of their diseases. Recommender systems can be a potential solution since they can be used to retrieve hig h quality health information provided by both patients and health professionals. There is a wide range of recommendation techniques based on opinions mining, tags and users? preferences, but few of them have been tested in the health domain.
Recommender systems have the advantage of crowd-sourcing, since knowledge is gathered about trustworthy sources while users seek information about a certain disease. The site suggests the most popular content or those that best correlate. Recommender systems gather d ata according to user preferences, opinions and other health measures.
The project Diabetes Health Recommender System (Diabetes HealthRecSys) helps users find useful, truthful and correct diabetes health information.
The main objective of this project is the creation of a diabetes video recommender system. A case study will take in consideration and extract the results comparing with other Internet video services. Additionally, it is necessary to deploy a video portal where diabetes videos will be int egrated. That video portal is already in a beta stage and will need to be further improved previous tests with real users. Finally, the project will perform several evaluation studies to compare the recommender systems developed with other Internet servi ces.