A framework to monitor clusters evolution applied to economy and finance problems
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://repositorio.inesctec.pt/handle/123456789/2520 http://dx.doi.org/10.3233/IDA-2011-0512 |
Resumo: | The study of evolution has become an important research issue, especially in the last decade, due to our ability to collect and store high detailed and time-stamped data. The need for describing and understanding the behavior of a given phenomena over time led to the emergence of new frameworks and methods focused on the temporal evolution of data and models. In this paper we address the problem of monitoring the evolution of clusters over time and propose the MEC framework. MEC traces evolution through the detection and categorization of clusters transitions, such as births, deaths and merges, and enables their visualization through bipartite graphs. It includes a taxonomy of transitions, a tracking method based in the computation of conditional probabilities, and a transition detection algorithm. We use MEC with two main goals: to determine the general evolution trends and to detect abnormal behavior or rare events. To demonstrate the applicability of our framework we present real wo |
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A framework to monitor clusters evolution applied to economy and finance problemsThe study of evolution has become an important research issue, especially in the last decade, due to our ability to collect and store high detailed and time-stamped data. The need for describing and understanding the behavior of a given phenomena over time led to the emergence of new frameworks and methods focused on the temporal evolution of data and models. In this paper we address the problem of monitoring the evolution of clusters over time and propose the MEC framework. MEC traces evolution through the detection and categorization of clusters transitions, such as births, deaths and merges, and enables their visualization through bipartite graphs. It includes a taxonomy of transitions, a tracking method based in the computation of conditional probabilities, and a transition detection algorithm. We use MEC with two main goals: to determine the general evolution trends and to detect abnormal behavior or rare events. To demonstrate the applicability of our framework we present real wo2017-11-16T13:46:57Z2012-01-01T00:00:00Z2012info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/2520http://dx.doi.org/10.3233/IDA-2011-0512engJoão GamaMárcia Barbosa Oliveirainfo: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:RCAAP2023-05-15T10:19:52Zoai:repositorio.inesctec.pt:123456789/2520Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:21.913315Repositório 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 |
A framework to monitor clusters evolution applied to economy and finance problems |
title |
A framework to monitor clusters evolution applied to economy and finance problems |
spellingShingle |
A framework to monitor clusters evolution applied to economy and finance problems João Gama |
title_short |
A framework to monitor clusters evolution applied to economy and finance problems |
title_full |
A framework to monitor clusters evolution applied to economy and finance problems |
title_fullStr |
A framework to monitor clusters evolution applied to economy and finance problems |
title_full_unstemmed |
A framework to monitor clusters evolution applied to economy and finance problems |
title_sort |
A framework to monitor clusters evolution applied to economy and finance problems |
author |
João Gama |
author_facet |
João Gama Márcia Barbosa Oliveira |
author_role |
author |
author2 |
Márcia Barbosa Oliveira |
author2_role |
author |
dc.contributor.author.fl_str_mv |
João Gama Márcia Barbosa Oliveira |
description |
The study of evolution has become an important research issue, especially in the last decade, due to our ability to collect and store high detailed and time-stamped data. The need for describing and understanding the behavior of a given phenomena over time led to the emergence of new frameworks and methods focused on the temporal evolution of data and models. In this paper we address the problem of monitoring the evolution of clusters over time and propose the MEC framework. MEC traces evolution through the detection and categorization of clusters transitions, such as births, deaths and merges, and enables their visualization through bipartite graphs. It includes a taxonomy of transitions, a tracking method based in the computation of conditional probabilities, and a transition detection algorithm. We use MEC with two main goals: to determine the general evolution trends and to detect abnormal behavior or rare events. To demonstrate the applicability of our framework we present real wo |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-01-01T00:00:00Z 2012 2017-11-16T13:46:57Z |
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://repositorio.inesctec.pt/handle/123456789/2520 http://dx.doi.org/10.3233/IDA-2011-0512 |
url |
http://repositorio.inesctec.pt/handle/123456789/2520 http://dx.doi.org/10.3233/IDA-2011-0512 |
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.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 |
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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 |
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1799131599963422720 |