Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/61586
Título: | A comparison of data-driven approaches for mobile marketing user conversion prediction |
Autor(es): | Matos, Luis Miguel Cortez, Paulo Mendes, Rui Moreau, Antoine |
Palavras-chave: | Classification Conversion Rate (CVR) Big Data Data Mining Mobile Performance Marketing |
Data: | Set-2018 |
Editora: | IEEE |
Resumo(s): | In this paper, we perform an exploratory study of user Conversion Rate (CVR) prediction using recent big data from a global mobile marketing company. We design a stream processing engine to collect sampled mobile marketing data. Then, we execute a large set of CVR prediction tests, under a two-stage experimental procedure that considers a rolling window evaluation. First, several preprocessing and machine learning combinations are analyzed using preliminary data. Next, the se- lected combinations are tested on a larger set of unseen datasets. Interesting classification performances were achieved, with some learning models (e.g., XGboost, Logistic Regression) requiring a reduced computational effort, thus showing a potential value for user CVR prediction in this domain. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/61586 |
ISBN: | 978-1-5386-7097-2 |
DOI: | 10.1109/IS.2018.8710472 |
Versão da editora: | Original publication is available at: https://ieeexplore.ieee.org/document/8710472 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Este trabalho está licenciado sob uma Licença Creative Commons