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Leveraging semantic networks for personalized content in health recommender systems
Abstract Since the emergence of the Internet in theSince the emergence of the Internet in the early 90's of the last century medical knowledge is spreading around the globe increasingly fast. Though publicly available, it is a difficult task to determine individual relevance for most non professionals. Additionally, relationships between medical terms are hard to discover even for professionals. In this paper we present an approach on how semantic query expansion can be exploited to enhance classic information retrieval (IR) techniques in order to gather health information artifacts for consumers. The approach is based on health related semantic networks which are automatically generated from public resources such as Wikipedia. A scenario for integrating such networks is a so-called health recommender systems (HRS) which can be embedded into a personal health record system (PHRS). This way, relevant personalized medical content can be delivered automatically to end users and owners of health records.to end users and owners of health records.
Abstractsub Since the emergence of the Internet in theSince the emergence of the Internet in the early 90's of the last century medical knowledge is spreading around the globe increasingly fast. Though publicly available, it is a difficult task to determine individual relevance for most non professionals. Additionally, relationships between medical terms are hard to discover even for professionals. In this paper we present an approach on how semantic query expansion can be exploited to enhance classic information retrieval (IR) techniques in order to gather health information artifacts for consumers. The approach is based on health related semantic networks which are automatically generated from public resources such as Wikipedia. A scenario for integrating such networks is a so-called health recommender systems (HRS) which can be embedded into a personal health record system (PHRS). This way, relevant personalized medical content can be delivered automatically to end users and owners of health records.to end users and owners of health records.
Bibtextype inproceedings  +
Doi 10.1109/CBMS.2011.5999164  +
Has author Wiesner M. + , Rotter S. + , Pfeifer D. +
Has extra keyword Automatically generated + , End users + , Health informations + , Health records + , Medical knowledge + , Medical terms + , Personal health record + , Personalized content + , Public resources + , Semantic network + , Semantic query expansion + , Wikipedia + , Embedded systems + , Knowledge management + , Recommender system + , Semantic web + , Semantics + , Health +
Isbn 9781457711909  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Published in Proceedings - IEEE Symposium on Computer-Based Medical Systems +
Title Leveraging semantic networks for personalized content in health recommender systems +
Type conference paper  +
Year 2011 +
Creation dateThis property is a special property in this wiki. 8 November 2014 00:29:19  +
Categories Publications without keywords parameter  + , Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 8 November 2014 00:29:19  +
DateThis property is a special property in this wiki. 2011  +
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