Adapting recommender systems to the requirements of personal health record systems
|Adapting recommender systems to the requirements of personal health record systems|
|Author(s)||Wiesner M., Pfeifer D.|
|Published in||IHI'10 - Proceedings of the 1st ACM International Health Informatics Symposium|
|Keyword(s)||graph theory, health care, information needs, knowledge mining, recommender systems, relevance computation, wikipedia (Extra: Information need, Knowledge mining, Recommender systems, relevance computation, Wikipedia, Data mining, Data structures, Graph theory, Health care, Information science, Semantics, Health)|
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Adapting recommender systems to the requirements of personal health record systems is a 2010 conference paper written in English by Wiesner M., Pfeifer D. and published in IHI'10 - Proceedings of the 1st ACM International Health Informatics Symposium.
In the future many people in industrialized countries will manage their personal health data electronically in centralized, reliable and trusted repositories - so-called personal health record systems (PHR). At this stage PHR systems still fail to satisfy the individual medical information needs of their users. Personalized recommendations could solve this problem. A first approach of integrating recommender system (RS) methodology into personal health records - termed health recommender system (HRS) - is presented. By exploitation of existing semantic networks like Wikipedia a health graph data structure is obtained. The data kept within such a graph represent health related concepts and are used to compute semantic distances among pairs of such concepts. A ranking procedure based on the health graph is outlined which enables a match between entries of a PHR system and health information artifacts. This way a PHR user will obtain individualized health information he might be interested in.
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