Data processing for direct marketing through Big Data
Traditional marketing performs promotion through various channels such as news in newspapers, radio, etc., but those promotions are aimed at all people, whether or not interested in the product or service being promoted. This method usually leads to high expenses and a low response rate by potential...
- Autores:
-
amelec, viloria
Varela, Noel
MALDONADO PEREZ, DOYREG
Pineda Lezama, Omar Bonerge
- Tipo de recurso:
- http://purl.org/coar/resource_type/c_816b
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/6185
- Acceso en línea:
- https://hdl.handle.net/11323/6185
https://repositorio.cuc.edu.co/
- Palabra clave:
- Data stream
WEKA
MOA
SAMOA
Big Data
Direct marketing
- Rights
- openAccess
- License
- CC0 1.0 Universal
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repository_id_str |
|
dc.title.spa.fl_str_mv |
Data processing for direct marketing through Big Data |
title |
Data processing for direct marketing through Big Data |
spellingShingle |
Data processing for direct marketing through Big Data Data stream WEKA MOA SAMOA Big Data Direct marketing |
title_short |
Data processing for direct marketing through Big Data |
title_full |
Data processing for direct marketing through Big Data |
title_fullStr |
Data processing for direct marketing through Big Data |
title_full_unstemmed |
Data processing for direct marketing through Big Data |
title_sort |
Data processing for direct marketing through Big Data |
dc.creator.fl_str_mv |
amelec, viloria Varela, Noel MALDONADO PEREZ, DOYREG Pineda Lezama, Omar Bonerge |
dc.contributor.author.spa.fl_str_mv |
amelec, viloria Varela, Noel MALDONADO PEREZ, DOYREG Pineda Lezama, Omar Bonerge |
dc.subject.spa.fl_str_mv |
Data stream WEKA MOA SAMOA Big Data Direct marketing |
topic |
Data stream WEKA MOA SAMOA Big Data Direct marketing |
description |
Traditional marketing performs promotion through various channels such as news in newspapers, radio, etc., but those promotions are aimed at all people, whether or not interested in the product or service being promoted. This method usually leads to high expenses and a low response rate by potential customers. That is why, nowadays, because there is a very competitive market, mass marketing is not safe, hence specialists are focusing efforts on direct marketing. This method studies the characteristics, needs and also selects a group of customers as a target for the promotion. Direct marketing uses predictive modeling from customer data, with the aim of selecting the most likely to respond to promotions. This research proposes a platform for the processing of data flows for target customer selection processes and the construction of required predictive response models. |
publishDate |
2020 |
dc.date.accessioned.none.fl_str_mv |
2020-04-14T20:32:36Z |
dc.date.available.none.fl_str_mv |
2020-04-14T20:32:36Z |
dc.date.issued.none.fl_str_mv |
2020-01-07 |
dc.type.spa.fl_str_mv |
Pre-Publicación |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_816b |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/preprint |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ARTOTR |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
format |
http://purl.org/coar/resource_type/c_816b |
status_str |
acceptedVersion |
dc.identifier.uri.spa.fl_str_mv |
https://hdl.handle.net/11323/6185 |
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/ |
url |
https://hdl.handle.net/11323/6185 https://repositorio.cuc.edu.co/ |
identifier_str_mv |
Corporación Universidad de la Costa REDICUC - Repositorio CUC |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.rights.spa.fl_str_mv |
CC0 1.0 Universal |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/publicdomain/zero/1.0/ |
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 |
CC0 1.0 Universal http://creativecommons.org/publicdomain/zero/1.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.publisher.spa.fl_str_mv |
Universidad de la Costa |
institution |
Corporación Universidad de la Costa |
bitstream.url.fl_str_mv |
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amelec, viloriaVarela, NoelMALDONADO PEREZ, DOYREGPineda Lezama, Omar Bonerge2020-04-14T20:32:36Z2020-04-14T20:32:36Z2020-01-07https://hdl.handle.net/11323/6185Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Traditional marketing performs promotion through various channels such as news in newspapers, radio, etc., but those promotions are aimed at all people, whether or not interested in the product or service being promoted. This method usually leads to high expenses and a low response rate by potential customers. That is why, nowadays, because there is a very competitive market, mass marketing is not safe, hence specialists are focusing efforts on direct marketing. This method studies the characteristics, needs and also selects a group of customers as a target for the promotion. Direct marketing uses predictive modeling from customer data, with the aim of selecting the most likely to respond to promotions. This research proposes a platform for the processing of data flows for target customer selection processes and the construction of required predictive response models.amelec, viloria-will be generated-orcid-0000-0003-2673-6350-600Varela, NoelMALDONADO PEREZ, DOYREG-will be generated-orcid-0000-0001-7448-654X-600Pineda Lezama, Omar BonergeengUniversidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Data streamWEKAMOASAMOABig DataDirect marketingData processing for direct marketing through Big DataPre-Publicaciónhttp://purl.org/coar/resource_type/c_816bTextinfo:eu-repo/semantics/preprinthttp://purl.org/redcol/resource_type/ARTOTRinfo:eu-repo/semantics/acceptedVersionPublicationORIGINALData Processing for Direct Marketing Through Big Data.pdfData Processing for Direct Marketing Through Big Data.pdfapplication/pdf75496https://repositorio.cuc.edu.co/bitstreams/880d378e-7dfc-4d63-bc18-4ee3ef615a57/downloadb59364f22aeb3f4ec263e67beb540ae8MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8701https://repositorio.cuc.edu.co/bitstreams/bd77338a-23f5-4614-8976-01a3d4261eb4/download42fd4ad1e89814f5e4a476b409eb708cMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/5a790ee4-4668-4eb1-906f-63fcab768f9c/download8a4605be74aa9ea9d79846c1fba20a33MD53THUMBNAILData Processing for Direct Marketing Through Big Data.pdf.jpgData Processing for Direct Marketing Through Big Data.pdf.jpgimage/jpeg41487https://repositorio.cuc.edu.co/bitstreams/835b30c7-628b-4f9d-99c4-e09de35d11d9/download9fe382f6318e3b43a703be186650a93cMD54TEXTData Processing for Direct Marketing Through Big Data.pdf.txtData Processing for Direct Marketing Through Big Data.pdf.txttext/plain1127https://repositorio.cuc.edu.co/bitstreams/449f6593-0649-4148-9159-3d376a82cc05/download213e2c09793885723b34bcc6cfe55ac1MD5511323/6185oai:repositorio.cuc.edu.co:11323/61852024-09-17 14:11:25.84http://creativecommons.org/publicdomain/zero/1.0/CC0 1.0 Universalopen.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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 |