How to detect a small cluster in big data?

Bibliographic Details
Main Author: João, Paulo
Publication Date: 2014
Other Authors: Lobo, Victor
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://doi.org/10.18803/capsi.v14.162-173
Summary: João, P., & Lobo, V. (2014). How to detect a small cluster in big data? In Atas da 14ª Conferência da Associação Portuguesa de Sistemas de Informação: Os Sistemas de Informação na Saúde (Vol. 14, pp. 162-173). (Atas da Conferencia da Associacao Portuguesa de Sistemas de Informacao). Fundação Luis de Molina. DOI: 10.18803/capsi.v14.162-173
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spelling How to detect a small cluster in big data?Big dataClusterData miningHSOMOutlier detectionSOMInformation Systems and ManagementManagement Information SystemsManagement of Technology and InnovationInformation SystemsComputer Science ApplicationsJoão, P., & Lobo, V. (2014). How to detect a small cluster in big data? In Atas da 14ª Conferência da Associação Portuguesa de Sistemas de Informação: Os Sistemas de Informação na Saúde (Vol. 14, pp. 162-173). (Atas da Conferencia da Associacao Portuguesa de Sistemas de Informacao). Fundação Luis de Molina. DOI: 10.18803/capsi.v14.162-173Detecting small clusters in a large amount of data is a difficult problem, mainly when there are only a few samples to be detected. There are general purpose solutions for small cluster detection, but many times they are not adequate for specific data. Artificial Intelligence techniques have been proposed, because they present the advantage of requiring little or no a priori assumption on the data distributions. The amount and higher dimensional nature of big data makes it too complex to be processed and analyzed by traditional methods. Hierarchical Self Organizing Maps, (HSOM) can improve the decision making with an approach based on specialization of Self Organizing Maps (SOM), dimensionality reduction and visualization of clusters. The goal is to propose a methodology to detect and visualize small clusters in the data with a toy case, where traditional human based approaches are not possible or are too complex to process, and the results clearly demonstrate that the HSOM based method outperforms the most widely adopted traditional methods revealing a number of small clusters hidden in data.Fundação Luis de MolinaNOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNJoão, PauloLobo, Victor2018-12-06T23:05:42Z2014-01-012014-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersion12application/pdfhttps://doi.org/10.18803/capsi.v14.162-173eng978-989-8132-13-0PURE: 6551787http://www.scopus.com/inward/record.url?scp=85047217407&partnerID=8YFLogxKhttps://doi.org/10.18803/capsi.v14.162-173info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:35:56Zoai:run.unl.pt:10362/53819Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:06:59.517901Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv How to detect a small cluster in big data?
title How to detect a small cluster in big data?
spellingShingle How to detect a small cluster in big data?
João, Paulo
Big data
Cluster
Data mining
HSOM
Outlier detection
SOM
Information Systems and Management
Management Information Systems
Management of Technology and Innovation
Information Systems
Computer Science Applications
title_short How to detect a small cluster in big data?
title_full How to detect a small cluster in big data?
title_fullStr How to detect a small cluster in big data?
title_full_unstemmed How to detect a small cluster in big data?
title_sort How to detect a small cluster in big data?
author João, Paulo
author_facet João, Paulo
Lobo, Victor
author_role author
author2 Lobo, Victor
author2_role author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv João, Paulo
Lobo, Victor
dc.subject.por.fl_str_mv Big data
Cluster
Data mining
HSOM
Outlier detection
SOM
Information Systems and Management
Management Information Systems
Management of Technology and Innovation
Information Systems
Computer Science Applications
topic Big data
Cluster
Data mining
HSOM
Outlier detection
SOM
Information Systems and Management
Management Information Systems
Management of Technology and Innovation
Information Systems
Computer Science Applications
description João, P., & Lobo, V. (2014). How to detect a small cluster in big data? In Atas da 14ª Conferência da Associação Portuguesa de Sistemas de Informação: Os Sistemas de Informação na Saúde (Vol. 14, pp. 162-173). (Atas da Conferencia da Associacao Portuguesa de Sistemas de Informacao). Fundação Luis de Molina. DOI: 10.18803/capsi.v14.162-173
publishDate 2014
dc.date.none.fl_str_mv 2014-01-01
2014-01-01T00:00:00Z
2018-12-06T23:05:42Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://doi.org/10.18803/capsi.v14.162-173
url https://doi.org/10.18803/capsi.v14.162-173
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-989-8132-13-0
PURE: 6551787
http://www.scopus.com/inward/record.url?scp=85047217407&partnerID=8YFLogxK
https://doi.org/10.18803/capsi.v14.162-173
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 12
application/pdf
dc.publisher.none.fl_str_mv Fundação Luis de Molina
publisher.none.fl_str_mv Fundação Luis de Molina
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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