Intellectual property in colombian museums: an application of machine learning
The purpose of this research is to answer the following guiding question: how can the behavior of museum networks in Colombia be predicted with respect to the protection of intellectual property (copyright, confidential information and use of patents, domain names, industrial designs, use of tradema...
- Autores:
-
Lis-Gutiérrez, Jenny-Paola
Zerda Sarmiento, Alvaro
amelec, viloria
- Tipo de recurso:
- http://purl.org/coar/resource_type/c_816b
- Fecha de publicación:
- 2019
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/5859
- Acceso en línea:
- https://hdl.handle.net/11323/5859
https://repositorio.cuc.edu.co/
- Palabra clave:
- Proximity
Intellectual property
Intellectual property management
Museum
Museum networks
Machine learning
- Rights
- openAccess
- License
- http://creativecommons.org/publicdomain/zero/1.0/
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| dc.title.spa.fl_str_mv |
Intellectual property in colombian museums: an application of machine learning |
| title |
Intellectual property in colombian museums: an application of machine learning |
| spellingShingle |
Intellectual property in colombian museums: an application of machine learning Proximity Intellectual property Intellectual property management Museum Museum networks Machine learning |
| title_short |
Intellectual property in colombian museums: an application of machine learning |
| title_full |
Intellectual property in colombian museums: an application of machine learning |
| title_fullStr |
Intellectual property in colombian museums: an application of machine learning |
| title_full_unstemmed |
Intellectual property in colombian museums: an application of machine learning |
| title_sort |
Intellectual property in colombian museums: an application of machine learning |
| dc.creator.fl_str_mv |
Lis-Gutiérrez, Jenny-Paola Zerda Sarmiento, Alvaro amelec, viloria |
| dc.contributor.author.spa.fl_str_mv |
Lis-Gutiérrez, Jenny-Paola Zerda Sarmiento, Alvaro amelec, viloria |
| dc.subject.spa.fl_str_mv |
Proximity Intellectual property Intellectual property management Museum Museum networks Machine learning |
| topic |
Proximity Intellectual property Intellectual property management Museum Museum networks Machine learning |
| description |
The purpose of this research is to answer the following guiding question: how can the behavior of museum networks in Colombia be predicted with respect to the protection of intellectual property (copyright, confidential information and use of patents, domain names, industrial designs, use of trademarks) and the interaction of different types of proximity (geographical, organizational, relational, cognitive, cultural and institutional), based on the use of supervised learning algorithms? Among the main findings are that the best learning algorithms to predict the behavior of networks, considering different target variables are the AdaBoost, the naive Bayes and CN2 rule inducer |
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2019 |
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2019 |
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2020-01-17T19:31:07Z |
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2020-01-17T19:31:07Z |
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Pre-Publicación |
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http://purl.org/coar/resource_type/c_816b |
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http://purl.org/coar/resource_type/c_816b |
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https://hdl.handle.net/11323/5859 |
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Corporación Universidad de la Costa |
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REDICUC - Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
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https://hdl.handle.net/11323/5859 https://repositorio.cuc.edu.co/ |
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Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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eng |
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eng |
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http://creativecommons.org/publicdomain/zero/1.0/ |
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info:eu-repo/semantics/openAccess |
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http://purl.org/coar/access_right/c_abf2 |
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http://creativecommons.org/publicdomain/zero/1.0/ http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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Universidad de la Costa |
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Corporación Universidad de la Costa |
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Lis-Gutiérrez, Jenny-PaolaZerda Sarmiento, Alvaroamelec, viloria2020-01-17T19:31:07Z2020-01-17T19:31:07Z2019https://hdl.handle.net/11323/5859Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The purpose of this research is to answer the following guiding question: how can the behavior of museum networks in Colombia be predicted with respect to the protection of intellectual property (copyright, confidential information and use of patents, domain names, industrial designs, use of trademarks) and the interaction of different types of proximity (geographical, organizational, relational, cognitive, cultural and institutional), based on the use of supervised learning algorithms? Among the main findings are that the best learning algorithms to predict the behavior of networks, considering different target variables are the AdaBoost, the naive Bayes and CN2 rule inducerLis Gutiérrez, Jenny Paola-will be generated-orcid-0000-0002-1438-7619-600Zerda Sarmiento, Alvaro-will be generated-orcid-0000-0003-2715-1813-600Amelec, Viloria-will be generated-orcid-0000-0003-2673-6350-600engUniversidad de la Costahttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2ProximityIntellectual propertyIntellectual property managementMuseumMuseum networksMachine learningIntellectual property in colombian museums: an application of machine learningPre-Publicaciónhttp://purl.org/coar/resource_type/c_816bTextinfo:eu-repo/semantics/preprinthttp://purl.org/redcol/resource_type/ARTOTRinfo:eu-repo/semantics/acceptedVersionPublicationORIGINALINTELLECTUAL PROPERTY IN COLOMBIAN MUSEUMS AN APPLICATION OF MACHINE LEARNING.pdfINTELLECTUAL PROPERTY IN COLOMBIAN MUSEUMS AN APPLICATION OF MACHINE LEARNING.pdfapplication/pdf6313https://repositorio.cuc.edu.co/bitstreams/236f684c-e3ea-4e24-91c6-852ffca93ec6/downloadc93638c3f2e0fbd8843a1e17b2e34b88MD54CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8701https://repositorio.cuc.edu.co/bitstreams/6fcfd8e7-976f-4b2b-b5f0-1451ad3256eb/download42fd4ad1e89814f5e4a476b409eb708cMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/ed773896-d242-4046-bdfd-4b9a7686583e/download8a4605be74aa9ea9d79846c1fba20a33MD55THUMBNAILINTELLECTUAL PROPERTY IN COLOMBIAN MUSEUMS AN APPLICATION OF MACHINE LEARNING.pdf.jpgINTELLECTUAL PROPERTY IN COLOMBIAN MUSEUMS AN APPLICATION OF MACHINE LEARNING.pdf.jpgimage/jpeg36832https://repositorio.cuc.edu.co/bitstreams/56b4182a-9826-4ca6-bf32-31488da58304/download4508c797577a04ff3607df37a8600fc8MD57TEXTINTELLECTUAL PROPERTY IN COLOMBIAN MUSEUMS AN APPLICATION OF MACHINE LEARNING.pdf.txtINTELLECTUAL PROPERTY IN COLOMBIAN MUSEUMS AN APPLICATION OF MACHINE LEARNING.pdf.txttext/plain990https://repositorio.cuc.edu.co/bitstreams/4c85620b-9fdd-4f8c-b476-dcdee00cc49b/downloadbbe27a3d37f40b2123dc535ba4193bf1MD5811323/5859oai:repositorio.cuc.edu.co:11323/58592024-09-17 10:57:03.371http://creativecommons.org/publicdomain/zero/1.0/open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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 |