Semantic Intelligence and Sentiment Analysis

Detalhes bibliográficos
Autor(a) principal: Macedo, Mario
Data de Publicação: 2015
Outros Autores: Billonet, Laurent
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10884/1364
Resumo: 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 [1], 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.
id RCAP_e77d2bd60f09226115b32bc660a9c098
oai_identifier_str oai:repositorio-cientifico.uatlantica.pt:10884/1364
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Semantic Intelligence and Sentiment AnalysisMulti-agent PlatformSentiment AnalysisIn 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 [1], 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.Proceedings of Med@Tel 20152018-09-07T12:27:24Z2015-04-01T00:00:00Z2015-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10884/1364engMacedo, MarioBillonet, Laurentinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-04T11:08:05Zoai:repositorio-cientifico.uatlantica.pt:10884/1364Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:29:55.417882Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Semantic Intelligence and Sentiment Analysis
title Semantic Intelligence and Sentiment Analysis
spellingShingle Semantic Intelligence and Sentiment Analysis
Macedo, Mario
Multi-agent Platform
Sentiment Analysis
title_short Semantic Intelligence and Sentiment Analysis
title_full Semantic Intelligence and Sentiment Analysis
title_fullStr Semantic Intelligence and Sentiment Analysis
title_full_unstemmed Semantic Intelligence and Sentiment Analysis
title_sort Semantic Intelligence and Sentiment Analysis
author Macedo, Mario
author_facet Macedo, Mario
Billonet, Laurent
author_role author
author2 Billonet, Laurent
author2_role author
dc.contributor.author.fl_str_mv Macedo, Mario
Billonet, Laurent
dc.subject.por.fl_str_mv Multi-agent Platform
Sentiment Analysis
topic Multi-agent Platform
Sentiment Analysis
description 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 [1], 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.
publishDate 2015
dc.date.none.fl_str_mv 2015-04-01T00:00:00Z
2015-04
2018-09-07T12:27:24Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10884/1364
url http://hdl.handle.net/10884/1364
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Proceedings of Med@Tel 2015
publisher.none.fl_str_mv Proceedings of Med@Tel 2015
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799136781082296320