Modern Information Retrieval
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
SemMed: Applying Semantic Web to Medical Recommendation Systems
INTENSIVE '09 Proceedings of the 2009 First International Conference on Intensive Applications and Services
Improving the effectiveness of collaborative recommendation with ontology-based user profiles
Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems
Reliable medical recommendation systems with patient privacy
Proceedings of the 1st ACM International Health Informatics Symposium
Recommender Systems Handbook
A transfer approach to detecting disease reporting events in blog social media
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
Making use of social media data in public health
Proceedings of the 21st international conference companion on World Wide Web
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In traditional Event-Based Surveillance systems, documents are continuously monitored for health threats detection and reporting, following a user-defined set of rules. This monitoring may result in a large set of events detected, overwhelming the user. In addition, such systems would not consider aspects similar to the user's set of defined rules other than exact matches. This prevents the user from discovering similar health threats that could also be of interest. In this paper, we perform a two-fold evaluation of a recommendation algorithm that infers the user preferences from his set of defined rules. In the first part of the evaluation, the participants evaluate the recommendations whether they match their interest in the H1N1 virus. For this evaluation, we achieved a precision rate of 0.81. In the second part, we conduct a group discussion with health surveillance experts where they provide feedback on the recommendations received. We present these results in terms of what should be recommended, and how the recommendations should be evaluated and take place in a surveillance system.