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|Title:||Semantic Intelligence and Sentiment Analysis|
|Publisher:||Proceedings of Med@Tel 2015|
|Citation:||• Macedo, M. & Billonet, Laurent (2015) . Semantic Intelligence and Sentiment Analysis. Proceedings of Med@Tel 2015 , Luxembourg.|
|Abstract:||In nowadays the domain of health data is composed by different dimensions with an emphasis in Electronic Health Records and also in Genomic, Public Health and Social Data among others. The enormous quantity of data provided from different sensors and communication languages forms what we call the Big Data of Health and Wellness. However, the unstructured data does not necessary conducts to information. The usage of Smart Technologies to promote information and knowledge is a very important issue for independent living and wellbeing. According with , intelligent data analysis applied to big data, presents the following challenges: a)Increase of sensor data volume (terabytes to exabytes); b)Heterogeneity: multiple data formats and standards, mix of structured and unstructured; c)Need to quickly acquire and process intelligence information; d)Agility is required to be able to incorporate new data sources; e)Support to data exploitation: each piece of data represents some part of a situation, intelligence data contain entities that must be understood and correlated. This paper presents a methodology validated by a case study to extract information from patients’ discharge notes.|
|Appears in Collections:||A CTIC/GSC - Artigos|
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