Creation of business profiles of exporting companies through unsupervised learning
This research presents a method for the creation of business profiles of export companies in the city of Barranquilla - Colombia. The method is supported by the development of unsupervised data learning techniques, Principal Component Analysis and Cluster analysis. The database used corresponds to p...
- Autores:
-
de la Hoz-Dominguez, Enrique J.
Escorcia-Guzman, Adalberto
Fontalvo-Herrera, Tomás J
- Tipo de recurso:
- Fecha de publicación:
- 2019
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/12336
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/12336
- Palabra clave:
- Bankruptcy Prediction;
Credit Scoring;
Prediction
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Creation of business profiles of exporting companies through unsupervised learning |
| dc.title.alternative.spa.fl_str_mv |
Creación de Perfiles Empresariales para Compañías Exportadoras mediante Aprendizaje No Supervisado |
| title |
Creation of business profiles of exporting companies through unsupervised learning |
| spellingShingle |
Creation of business profiles of exporting companies through unsupervised learning Bankruptcy Prediction; Credit Scoring; Prediction LEMB |
| title_short |
Creation of business profiles of exporting companies through unsupervised learning |
| title_full |
Creation of business profiles of exporting companies through unsupervised learning |
| title_fullStr |
Creation of business profiles of exporting companies through unsupervised learning |
| title_full_unstemmed |
Creation of business profiles of exporting companies through unsupervised learning |
| title_sort |
Creation of business profiles of exporting companies through unsupervised learning |
| dc.creator.fl_str_mv |
de la Hoz-Dominguez, Enrique J. Escorcia-Guzman, Adalberto Fontalvo-Herrera, Tomás J |
| dc.contributor.author.none.fl_str_mv |
de la Hoz-Dominguez, Enrique J. Escorcia-Guzman, Adalberto Fontalvo-Herrera, Tomás J |
| dc.subject.keywords.spa.fl_str_mv |
Bankruptcy Prediction; Credit Scoring; Prediction |
| topic |
Bankruptcy Prediction; Credit Scoring; Prediction LEMB |
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LEMB |
| description |
This research presents a method for the creation of business profiles of export companies in the city of Barranquilla - Colombia. The method is supported by the development of unsupervised data learning techniques, Principal Component Analysis and Cluster analysis. The database used corresponds to primary financial information of 107 companies registered in the Chamber of Commerce of Barranquilla. First, a review of the context of global and local exports is presented. Next, the analysis of components allowed the creation of new uncorrelated variables and the joint visualization of variables in a two-dimensional space. Subsequently, the cluster analysis of the companies was interpreted in the cluster analysis according to the financial items studied. The work shows that the methodology employed allows identifying the type of service that an enterprise needs to achieve the best levels of performance, which in turns facilitates the implementation of development plans and of public and private policies of business promotion. © 2019 Centro de Informacion Tecnologica. All rights reserved. |
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2019 |
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2019 |
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2023-07-21T16:23:46Z |
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2023-07-21T16:23:46Z |
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2023 |
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Hoz-Dominguez, E. J., Fontalvo-Herrera, T. J., & Escorcia-Guzman, A. (2019). Creación de perfiles empresariales para compañías exportadoras mediante aprendizaje no supervisado. Información tecnológica, 30(6), 193-200. |
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https://hdl.handle.net/20.500.12585/12336 |
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10.4067/S0718-07642019000600193 |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
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Hoz-Dominguez, E. J., Fontalvo-Herrera, T. J., & Escorcia-Guzman, A. (2019). Creación de perfiles empresariales para compañías exportadoras mediante aprendizaje no supervisado. Información tecnológica, 30(6), 193-200. 10.4067/S0718-07642019000600193 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
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https://hdl.handle.net/20.500.12585/12336 |
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spa |
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spa |
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de la Hoz-Dominguez, Enrique J.d116a7bd-b3e2-454d-9181-c05da0ae89c5Escorcia-Guzman, Adalbertoab41d5b6-0e82-4a65-878e-b9af5a8788a1Fontalvo-Herrera, Tomás Jb4a83ba0-1619-434e-8343-75af19900fe22023-07-21T16:23:46Z2023-07-21T16:23:46Z20192023Hoz-Dominguez, E. J., Fontalvo-Herrera, T. J., & Escorcia-Guzman, A. (2019). Creación de perfiles empresariales para compañías exportadoras mediante aprendizaje no supervisado. Información tecnológica, 30(6), 193-200.https://hdl.handle.net/20.500.12585/1233610.4067/S0718-07642019000600193Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis research presents a method for the creation of business profiles of export companies in the city of Barranquilla - Colombia. The method is supported by the development of unsupervised data learning techniques, Principal Component Analysis and Cluster analysis. The database used corresponds to primary financial information of 107 companies registered in the Chamber of Commerce of Barranquilla. First, a review of the context of global and local exports is presented. Next, the analysis of components allowed the creation of new uncorrelated variables and the joint visualization of variables in a two-dimensional space. Subsequently, the cluster analysis of the companies was interpreted in the cluster analysis according to the financial items studied. The work shows that the methodology employed allows identifying the type of service that an enterprise needs to achieve the best levels of performance, which in turns facilitates the implementation of development plans and of public and private policies of business promotion. © 2019 Centro de Informacion Tecnologica. All rights reserved.8 páginasapplication/pdfspahttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Informacion TecnologicaCreation of business profiles of exporting companies through unsupervised learningCreación de Perfiles Empresariales para Compañías Exportadoras mediante Aprendizaje No Supervisadoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_2df8fbb1Bankruptcy Prediction;Credit Scoring;PredictionLEMBCartagena de IndiasAhlemeyer-Stubbe, A., Horvath, S. (2016) Intelligent Profiles and Segments Equals Pure Power for Business: Combining Profiles, Segment and Predictive AnalyticsAlvarez, E.P., Suarez, J.E. La generación de beneficios sociales y económicos de las zonas francas en Colombia face (2016) Revista De La Facultad De Ciencias Económicas Y Empresariales, 15 (2), pp. 53-67.Ansari, A., Riasi, A. Modelling and evaluating customer loyalty using neural networks: Evidence from startup insurance companies (2016) Future Business Journal, 2 (1), pp. 15-30. Cited 51 times.Bogh, S.B., Falstie-Jensen, A.M., Hollnagel, E., Holst, R., Braithwaite, J., Johnsen, S.P. Improvement in quality of hospital care during accreditation: A nationwide stepped-wedge study (2016) International Journal for Quality in Health Care, 28 (6), pp. 715-720. Cited 45 times. http://intqhc.oxfordjournals.org/ doi: 10.1093/intqhc/mzw099Bray, J.R., Curtis, J.T. (1957) An Ordination of the Upland Forest Communities of Southern Wisconsin Ecological Monographs, 27 (4), pp. 325-349. Cited 7485 times.De La Hoz, E., Polo, L.L. Application of cluster analysis techniques and artificial neural networks for the evaluation of the exporting capability of a company (2017) Informacion Tecnologica, 28 (4), pp. 67-74. Cited 13 times. http://www.scielo.cl/pdf/infotec/v28n4/art09.pdf doi: 10.4067/S0718-07642017000400009Dokmanic, I., Parhizkar, R., Ranieri, J., Vetterli, M. Euclidean Distance Matrices: Essential theory, algorithms, and applications (2015) IEEE Signal Processing Magazine, 32 (6), art. no. 7298562, pp. 12-30. Cited 312 times. http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=79&year=2008 doi: 10.1109/MSP.2015.2398954Fontalvo-Herrera, T.J., Delahoz, E.J., Mendoza-Mendoza, A.A. Application of data mining for the classification of university programs of industrial engineering accredited in high quality in Colombia (2018) Informacion Tecnologica, 29 (3), pp. 89-96. Cited 12 times. https://scielo.conicyt.cl/pdf/infotec/v29n3/0718-0764-infotec-29-03-00089.pdf doi: 10.4067/S0718-07642018000300089Fontalvo, T., De La Hoz, E., De La Hoz, E. Data envelopment analysis method and neural networks in the evaluation and prediction of the technical efficiency of small exporting companies (2018) Informacion Tecnologica, 29 (6), pp. 267-276. Cited 9 times. https://scielo.conicyt.cl/pdf/infotec/v29n6/0718-0764-infotec-29-06-00267.pdf doi: 10.4067/S0718-07642018000600267Gower, J.C. A general coefficient of similarity and some of its properties (1971) Biometrics, 27 (4), pp. 857-871. Cited 3160 times.Hinkelmann, K., Gerber, A., Karagiannis, D., Thoenssen, B., Van Der Merwe, A., Woitsch, R. A new paradigm for the continuous alignment of business and IT: Combining enterprise architecture modelling and enterprise ontology (2016) Computers in Industry, 79, pp. 77-86. Cited 127 times. doi: 10.1016/j.compind.2015.07.009Hosseinzadeh, A., Smyth, R., Valadkhani, A., Le, V. Analyzing the efficiency performance of major Australian mining companies using bootstrap data envelopment analysis (2016) Economic Modelling, 57, pp. 26-35. Cited 42 times. http://www.elsevier.com/locate/econmod doi: 10.1016/j.econmod.2016.04.008Hotelling, H. Analysis of a complex of statistical variables into principal components (1933) Journal of Educational Psychology, 24 (6), pp. 417-441. Cited 5318 times. doi: 10.1037/h0071325Kotsiantis, S.B., Zaharakis, I., Pintelas, P. Supervised machine learning: A review of classification techniques (2007) Emerging Artificial Intelligence Applications in Computer Engineering, 160, pp. 3-24. Cited 1795 times.Lambert, S.C., Davidson, R.A. 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Cited 22 times. https://academic.oup.com/cybersecurity doi: 10.1093/cybsec/tyw004Sathya, R., Abraham, A. Comparison of supervised and unsupervised learning algorithms for pattern classification (2013) International Journal of Advanced Research in Artificial Intelligence, 2 (2), pp. 34-38. Cited 243 times.Shahnoori, P., Jenkins, G.P. The value of online banking to small and medium-sized enterprises: evidence from firms operating in the uae free trade zones (Open Access) (2019) Applied Economics, 51 (37), pp. 4046-4055. Cited 5 times. http://www.tandfonline.com/toc/raec20/current doi: 10.1080/00036846.2019.1588948Stoica, O., Mehdian, S., Sargu, A. The impact of internet banking on the performance of Romanian banks: DEA and PCA approach (2015) Procedia Economics and Finance, 20, pp. 610-622. Cited 48 times.Swedberg, R. Can You Visualize Theory? on the Use of Visual Thinking in Theory Pictures, Theorizing Diagrams, and Visual Sketches (2016) Sociological Theory, 34 (3), pp. 250-275. 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