SSTS: A syntactic tool for pattern search on time series

Detalhes bibliográficos
Autor(a) principal: Rodrigues, João
Data de Publicação: 2019
Outros Autores: Folgado, Duarte, Belo, David, Gamboa, Hugo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/148743
Resumo: We would like to acknowledge the financial support obtained from North Portugal Regional Operational Programme (NORTE 2020), Portugal 2020 and the European Regional Development Fund (ERDF) from European Union through the project Symbiotic technology for societal efficiency gains: Deus ex Machina (DEM), NORTE-01-0145-FEDER-000026. We would like to acknowledge as well the projects AHA CMUP-ERI/HCI/0046 and INSIDE CMUP-ERI/HCI/051/2013 both financed by Fundcao para a Ciencia e Tecnologia (FCT).
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spelling SSTS: A syntactic tool for pattern search on time seriesGrammarMeta symbolic languageQuery searchRegular expressionSignal processingTime seriesInformation SystemsMedia TechnologyComputer Science ApplicationsManagement Science and Operations ResearchLibrary and Information SciencesWe would like to acknowledge the financial support obtained from North Portugal Regional Operational Programme (NORTE 2020), Portugal 2020 and the European Regional Development Fund (ERDF) from European Union through the project Symbiotic technology for societal efficiency gains: Deus ex Machina (DEM), NORTE-01-0145-FEDER-000026. We would like to acknowledge as well the projects AHA CMUP-ERI/HCI/0046 and INSIDE CMUP-ERI/HCI/051/2013 both financed by Fundcao para a Ciencia e Tecnologia (FCT).Nowadays, data scientists are capable of manipulating and extracting complex information from time series data, given the current diversity of tools at their disposal. However, the plethora of tools that target data exploration and pattern search may require an extensive amount of time to develop methods that correspond to the data scientist's reasoning, in order to solve their queries. The development of new methods, tightly related with the reasoning and visual analysis of time series data, is of great relevance to improving complexity and productivity of pattern and query search tasks. In this work, we propose a novel tool, capable of exploring time series data for pattern and query search tasks in a set of 3 symbolic steps: Pre-Processing, Symbolic Connotation and Search. The framework is called SSTS (Symbolic Search in Time Series) and uses regular expression queries to search the desired patterns in a symbolic representation of the signal. By adopting a set of symbolic methods, this approach has the purpose of increasing the expressiveness in solving standard pattern and query tasks, enabling the creation of queries more closely related to the reasoning and visual analysis of the signal. We demonstrate the tool's effectiveness by presenting 9 examples with several types of queries on time series. The SSTS queries were compared with standard code developed in Python, in terms of cognitive effort, vocabulary required, code length, volume, interpretation and difficulty metrics based on the Halstead complexity measures. The results demonstrate that this methodology is a valid approach and delivers a new abstraction layer on data analysis of time series.DF – Departamento de FísicaLIBPhys-UNLRUNRodrigues, JoãoFolgado, DuarteBelo, DavidGamboa, Hugo2023-02-06T22:14:53Z2019-01-012019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article16application/pdfhttp://hdl.handle.net/10362/148743eng0306-4573PURE: 11710926https://doi.org/10.1016/j.ipm.2018.09.001info: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:RCAAP2024-03-11T05:30:24Zoai:run.unl.pt:10362/148743Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:53:28.155791Repositório 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 SSTS: A syntactic tool for pattern search on time series
title SSTS: A syntactic tool for pattern search on time series
spellingShingle SSTS: A syntactic tool for pattern search on time series
Rodrigues, João
Grammar
Meta symbolic language
Query search
Regular expression
Signal processing
Time series
Information Systems
Media Technology
Computer Science Applications
Management Science and Operations Research
Library and Information Sciences
title_short SSTS: A syntactic tool for pattern search on time series
title_full SSTS: A syntactic tool for pattern search on time series
title_fullStr SSTS: A syntactic tool for pattern search on time series
title_full_unstemmed SSTS: A syntactic tool for pattern search on time series
title_sort SSTS: A syntactic tool for pattern search on time series
author Rodrigues, João
author_facet Rodrigues, João
Folgado, Duarte
Belo, David
Gamboa, Hugo
author_role author
author2 Folgado, Duarte
Belo, David
Gamboa, Hugo
author2_role author
author
author
dc.contributor.none.fl_str_mv DF – Departamento de Física
LIBPhys-UNL
RUN
dc.contributor.author.fl_str_mv Rodrigues, João
Folgado, Duarte
Belo, David
Gamboa, Hugo
dc.subject.por.fl_str_mv Grammar
Meta symbolic language
Query search
Regular expression
Signal processing
Time series
Information Systems
Media Technology
Computer Science Applications
Management Science and Operations Research
Library and Information Sciences
topic Grammar
Meta symbolic language
Query search
Regular expression
Signal processing
Time series
Information Systems
Media Technology
Computer Science Applications
Management Science and Operations Research
Library and Information Sciences
description We would like to acknowledge the financial support obtained from North Portugal Regional Operational Programme (NORTE 2020), Portugal 2020 and the European Regional Development Fund (ERDF) from European Union through the project Symbiotic technology for societal efficiency gains: Deus ex Machina (DEM), NORTE-01-0145-FEDER-000026. We would like to acknowledge as well the projects AHA CMUP-ERI/HCI/0046 and INSIDE CMUP-ERI/HCI/051/2013 both financed by Fundcao para a Ciencia e Tecnologia (FCT).
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01
2019-01-01T00:00:00Z
2023-02-06T22:14:53Z
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/10362/148743
url http://hdl.handle.net/10362/148743
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0306-4573
PURE: 11710926
https://doi.org/10.1016/j.ipm.2018.09.001
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 16
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
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
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