Toward semantic understanding: an approach based on information extraction ontologies
ADC '04 Proceedings of the 15th Australasian database conference - Volume 27
GATE: an architecture for development of robust HLT applications
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Designing ETL processes using semantic web technologies
DOLAP '06 Proceedings of the 9th ACM international workshop on Data warehousing and OLAP
Extraction and use of linguistic patterns for modelling medical guidelines
Artificial Intelligence in Medicine
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
The effects of source credibility ratings in a cultural heritage information aggregator
Proceedings of the 3rd workshop on Information credibility on the web
Ontology-based information extraction for business intelligence
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Ontology-based information extraction: An introduction and a survey of current approaches
Journal of Information Science
Design and evaluation of an ontology based information extraction system for radiological reports
Computers in Biology and Medicine
Social infobuttons: integrating open health data with social data using semantic technology
Proceedings of the Fifth Workshop on Semantic Web Information Management
Patient-centric, multi-role, and multi-dimension information exploration on online healthcare forums
Proceedings of the sixth workshop on Ph.D. students in information and knowledge management
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This project addresses how to link scattered health-related data from different Web communities, and provide integrated knowledge of health information. Specifically, we integrate data from social media-based patient communities, curated sites with expert content, and the research community. Our approach is based on medical concept extraction using the Unified Medical Language System (UMLS), Resource Description Framework (RDF) semantic modeling to represent diverse social health and medical experiences, and summarization of integrated health data. A prototype implementation annotates medical terms occurring in blogs with summarized health experience data, medical expert data and medical research data that enables users, such as patients, doctors or other health care providers to have integrated and linked view of health-related knowledge. Currently, the system integrates information from PatientsLikeMe, WebMD, and PubMed, and can be used to annotate a wide variety of text based blogs. This system uses ontology-based information extraction and semantic modeling of social health data to integrate informally specified information, which is typical of content written by patients.