Improving the quality of user generated data sets for activity recognition
It is fully appreciated that progress in the development of data driven approaches to activity recognition are being hampered due to the lack of large scale, high quality, annotated data sets. In an effort to address this the Open Data Initiative (ODI) was conceived as a potential solution for the c...
- Autores:
-
Nugent, Chris D.
Synnott, Jonathan
Gabrielli, Celeste
Zhang, Shuai
Espinilla, Macarena
Calzada, Alberto
Lundström, Jens
Cleland, Ian
Synnes, Kåre
Hallberg, Josef
Spinsante, Susanna
Ortiz Barrios, Miguel Angel
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2016
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/1387
- Acceso en línea:
- http://hdl.handle.net/11323/1387
https://repositorio.cuc.edu.co/
- Palabra clave:
- Activity recognition
Data driven classification
Data validation
Open data sets
- Rights
- openAccess
- License
- Atribución – No comercial – Compartir igual
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oai:repositorio.cuc.edu.co:11323/1387 |
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REDICUC - Repositorio CUC |
repository_id_str |
|
dc.title.eng.fl_str_mv |
Improving the quality of user generated data sets for activity recognition |
title |
Improving the quality of user generated data sets for activity recognition |
spellingShingle |
Improving the quality of user generated data sets for activity recognition Activity recognition Data driven classification Data validation Open data sets |
title_short |
Improving the quality of user generated data sets for activity recognition |
title_full |
Improving the quality of user generated data sets for activity recognition |
title_fullStr |
Improving the quality of user generated data sets for activity recognition |
title_full_unstemmed |
Improving the quality of user generated data sets for activity recognition |
title_sort |
Improving the quality of user generated data sets for activity recognition |
dc.creator.fl_str_mv |
Nugent, Chris D. Synnott, Jonathan Gabrielli, Celeste Zhang, Shuai Espinilla, Macarena Calzada, Alberto Lundström, Jens Cleland, Ian Synnes, Kåre Hallberg, Josef Spinsante, Susanna Ortiz Barrios, Miguel Angel |
dc.contributor.author.spa.fl_str_mv |
Nugent, Chris D. Synnott, Jonathan Gabrielli, Celeste Zhang, Shuai Espinilla, Macarena Calzada, Alberto Lundström, Jens Cleland, Ian Synnes, Kåre Hallberg, Josef Spinsante, Susanna Ortiz Barrios, Miguel Angel |
dc.subject.eng.fl_str_mv |
Activity recognition Data driven classification Data validation Open data sets |
topic |
Activity recognition Data driven classification Data validation Open data sets |
description |
It is fully appreciated that progress in the development of data driven approaches to activity recognition are being hampered due to the lack of large scale, high quality, annotated data sets. In an effort to address this the Open Data Initiative (ODI) was conceived as a potential solution for the creation of shared resources for the collection and sharing of open data sets. As part of this process, an analysis was undertaken of datasets collected using a smart environment simulation tool. A noticeable difference was found in the first 1–2 cycles of users generating data. Further analysis demonstrated the effects that this had on the development of activity recognition models with a decrease of performance for both support vector machine and decision tree based classifiers. The outcome of the study has led to the production of a strategy to ensure an initial training phase is considered prior to full scale collection of the data. |
publishDate |
2016 |
dc.date.issued.none.fl_str_mv |
2016 |
dc.date.accessioned.none.fl_str_mv |
2018-11-20T12:37:15Z |
dc.date.available.none.fl_str_mv |
2018-11-20T12:37:15Z |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ART |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
format |
http://purl.org/coar/resource_type/c_6501 |
status_str |
acceptedVersion |
dc.identifier.isbn.spa.fl_str_mv |
978-331948798-4 |
dc.identifier.issn.spa.fl_str_mv |
03029743 |
dc.identifier.uri.spa.fl_str_mv |
http://hdl.handle.net/11323/1387 |
dc.identifier.doi.spa.fl_str_mv |
10.1007/978-3-319-48799-1_13 |
dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
dc.identifier.reponame.spa.fl_str_mv |
REDICUC - Repositorio CUC |
dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.cuc.edu.co/ |
identifier_str_mv |
978-331948798-4 03029743 10.1007/978-3-319-48799-1_13 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
url |
http://hdl.handle.net/11323/1387 https://repositorio.cuc.edu.co/ |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.rights.spa.fl_str_mv |
Atribución – No comercial – Compartir igual |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.coar.spa.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
rights_invalid_str_mv |
Atribución – No comercial – Compartir igual http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
institution |
Corporación Universidad de la Costa |
bitstream.url.fl_str_mv |
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bitstream.checksumAlgorithm.fl_str_mv |
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repository.name.fl_str_mv |
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spelling |
Nugent, Chris D.ed15a0ac96fa8094ba07d995645a8345Synnott, Jonathan54debdad3dadcfc247bc8af9e3e10a77Gabrielli, Celeste5463e7b91fa9d24f7c3a4d15ce580595Zhang, Shuai90dce85e46fd92b6fafa2ae54ff32d40Espinilla, Macarena6959f57a40331a0516fbed8e07dc9c01Calzada, Alberto1135a8d195ee2e1e818c2f101e0b2f31Lundström, Jense93e06c0cca100160a52c157bde06ac1Cleland, Ian52c86c94b09dc567ee2901bc5b1c5b7dSynnes, Kåre3a61e6146165b5dcb5b184a425b4525bHallberg, Josefd430bd1cda9fbd79641a020cf5422c77Spinsante, Susanna20307b8e9c4f14acb2361da94948291eOrtiz Barrios, Miguel Angel0194f6a9674b28ba0ae84402ee76f9e42018-11-20T12:37:15Z2018-11-20T12:37:15Z2016978-331948798-403029743http://hdl.handle.net/11323/138710.1007/978-3-319-48799-1_13Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/It is fully appreciated that progress in the development of data driven approaches to activity recognition are being hampered due to the lack of large scale, high quality, annotated data sets. In an effort to address this the Open Data Initiative (ODI) was conceived as a potential solution for the creation of shared resources for the collection and sharing of open data sets. As part of this process, an analysis was undertaken of datasets collected using a smart environment simulation tool. A noticeable difference was found in the first 1–2 cycles of users generating data. Further analysis demonstrated the effects that this had on the development of activity recognition models with a decrease of performance for both support vector machine and decision tree based classifiers. The outcome of the study has led to the production of a strategy to ensure an initial training phase is considered prior to full scale collection of the data.engAtribución – No comercial – Compartir igualinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Activity recognitionData driven classificationData validationOpen data setsImproving the quality of user generated data sets for activity recognitionArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionORIGINALImproving the quality of user generated data sets.pdfImproving the quality of user generated data sets.pdfapplication/pdf276723https://repositorio.cuc.edu.co/bitstream/11323/1387/1/Improving%20the%20quality%20of%20user%20generated%20data%20sets.pdfd9caa657058160495f47ecb3e3f3059cMD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstream/11323/1387/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52open accessTHUMBNAILImproving the quality of user generated data sets.pdf.jpgImproving the quality of user generated data sets.pdf.jpgimage/jpeg41324https://repositorio.cuc.edu.co/bitstream/11323/1387/4/Improving%20the%20quality%20of%20user%20generated%20data%20sets.pdf.jpg34dcbab371c03dae02e2867b7a989596MD54open accessTEXTImproving the quality of user generated data sets.pdf.txtImproving the quality of user generated data sets.pdf.txttext/plain1377https://repositorio.cuc.edu.co/bitstream/11323/1387/5/Improving%20the%20quality%20of%20user%20generated%20data%20sets.pdf.txt266d28d0760dbae781e672613ff0a568MD55open access11323/1387oai:repositorio.cuc.edu.co:11323/13872023-12-14 17:10:41.152open accessRepositorio Universidad de La Costabdigital@metabiblioteca.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 |