Using neuroevolution for predicting mobile marketing conversion

Bibliographic Details
Main Author: Pereira, Pedro José
Publication Date: 2019
Other Authors: Pinto, Pedro, Mendes, Rui, Cortez, Paulo, Moreau, Antoine
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://hdl.handle.net/1822/62746
Summary: This paper addresses user Conversion Rate (CVR) prediction within the context of Mobile Performance Marketing. Specifically, we adapt two main neuroevolution methods: Neuroevolution of Augmenting Topologies (NEAT) and Hypercube-based NEAT (HyperNEAT). First, we discuss two mechanisms for increasing execution speed (parallelism and data sampling); a strategy for preventing excessive network complexity with NEAT; and a rolling window scheme for performing an online learning. Then, we present experimental results, using distinct datasets and testing both offline and online learning environments.
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spelling Using neuroevolution for predicting mobile marketing conversionClassificationMarketingNeuroevolutionScience & TechnologyThis paper addresses user Conversion Rate (CVR) prediction within the context of Mobile Performance Marketing. Specifically, we adapt two main neuroevolution methods: Neuroevolution of Augmenting Topologies (NEAT) and Hypercube-based NEAT (HyperNEAT). First, we discuss two mechanisms for increasing execution speed (parallelism and data sampling); a strategy for preventing excessive network complexity with NEAT; and a rolling window scheme for performing an online learning. Then, we present experimental results, using distinct datasets and testing both offline and online learning environments.ThisarticleisaresultoftheprojectNORTE-01-0247-FEDER-017497,supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This work was also supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019.Springer VerlagUniversidade do MinhoPereira, Pedro JoséPinto, PedroMendes, RuiCortez, PauloMoreau, Antoine20192019-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/1822/62746eng97830303024360302-974310.1007/978-3-030-30244-3_31https://link.springer.com/chapter/10.1007%2F978-3-030-30244-3_31info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T05:25:23Zoai:repositorium.sdum.uminho.pt:1822/62746Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T15:18:03.345256Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Using neuroevolution for predicting mobile marketing conversion
title Using neuroevolution for predicting mobile marketing conversion
spellingShingle Using neuroevolution for predicting mobile marketing conversion
Pereira, Pedro José
Classification
Marketing
Neuroevolution
Science & Technology
title_short Using neuroevolution for predicting mobile marketing conversion
title_full Using neuroevolution for predicting mobile marketing conversion
title_fullStr Using neuroevolution for predicting mobile marketing conversion
title_full_unstemmed Using neuroevolution for predicting mobile marketing conversion
title_sort Using neuroevolution for predicting mobile marketing conversion
author Pereira, Pedro José
author_facet Pereira, Pedro José
Pinto, Pedro
Mendes, Rui
Cortez, Paulo
Moreau, Antoine
author_role author
author2 Pinto, Pedro
Mendes, Rui
Cortez, Paulo
Moreau, Antoine
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Pereira, Pedro José
Pinto, Pedro
Mendes, Rui
Cortez, Paulo
Moreau, Antoine
dc.subject.por.fl_str_mv Classification
Marketing
Neuroevolution
Science & Technology
topic Classification
Marketing
Neuroevolution
Science & Technology
description This paper addresses user Conversion Rate (CVR) prediction within the context of Mobile Performance Marketing. Specifically, we adapt two main neuroevolution methods: Neuroevolution of Augmenting Topologies (NEAT) and Hypercube-based NEAT (HyperNEAT). First, we discuss two mechanisms for increasing execution speed (parallelism and data sampling); a strategy for preventing excessive network complexity with NEAT; and a rolling window scheme for performing an online learning. Then, we present experimental results, using distinct datasets and testing both offline and online learning environments.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-01-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1822/62746
url https://hdl.handle.net/1822/62746
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 9783030302436
0302-9743
10.1007/978-3-030-30244-3_31
https://link.springer.com/chapter/10.1007%2F978-3-030-30244-3_31
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833595229148545024

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