Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/62771
Título: | Using deep learning for mobile marketing user conversion prediction |
Autor(es): | Matos, Luís Miguel Cortez, Paulo Mendes, Rui Moreau, Antoine |
Palavras-chave: | Big Data Categorical Transformation Classification Conversion Rate (CVR) Mobile Performance Marketing Multilayer Perceptron. |
Data: | 2019 |
Editora: | IEEE Institute of Electrical and Electronics Engineers Inc. |
Revista: | IEEE International Joint Conference on Neural Networks (IJCNN) |
Resumo(s): | Mobile performance marketing is a growing industry due to the massive adoption of smartphones and tablets. In this paper, we explore Deep Multilayer Perceptrons (MLP) to predict the Conversion Rate (CVR) of mobile users that are redirected to ad campaigns (i.e., if there will be a sale). We analyze recent real-world big data provided by a global mobile marketing company. Using a realistic rolling window validation, we conducted several experiments with different datasets (two sampling and two data traffic modes), in which we measure both the predictive binary classification performance and the computational effort. The modeling experiments include: two data preprocessing methods, the popular one-hot encoding and a proposed Percentage Categorical Pruning (PCP); and two MLP learning modes, offline (reset) and online (reuse). Overall, competitive classification results were achieved by the PCP transform and the two MLP learning modes, producing real-time predictions and comparing favorably against a Convolutional Neural Network and a Logistic Regression. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/62771 |
ISBN: | 9781728119854 |
DOI: | 10.1109/IJCNN.2019.8851888 |
ISSN: | 2161-4393 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
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Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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afinal19327.pdf Acesso restrito! | Author's Accepted Manuscript | 278,64 kB | Adobe PDF | Ver/Abrir |