Comparison of Feature Extraction Methods and Predictors for Income Inference

Abstract—Patterns of mobile phone communications, coupled with the information of the social network graph and financial behavior, allow us to make inferences of users’ socio-economic attributes such as their income level. We present here several methods to extract features from mobile phone usage (...

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Detalles Bibliográficos
Autores principales: Fixman, Martín, Minnoni, Martín, Sarraute, Carlos
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2017
Materias:
Ciencias Informáticas
Teléfono Celular
aprendizaje automático
método bayesiano
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/63174
http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/AGRANDA/AGRANDA-06.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-63174
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Teléfono Celular
aprendizaje automático
método bayesiano
spellingShingle Ciencias Informáticas
Teléfono Celular
aprendizaje automático
método bayesiano
Fixman, Martín
Minnoni, Martín
Sarraute, Carlos
Comparison of Feature Extraction Methods and Predictors for Income Inference
topic_facet Ciencias Informáticas
Teléfono Celular
aprendizaje automático
método bayesiano
description Abstract—Patterns of mobile phone communications, coupled with the information of the social network graph and financial behavior, allow us to make inferences of users’ socio-economic attributes such as their income level. We present here several methods to extract features from mobile phone usage (calls and messages), and compare different combinations of supervised machine learning techniques and sets of features used as input for the inference of users’ income. Our experimental results show that the Bayesian method based on the communication graph outperforms standard machine learning algorithms using nodebased features.
format Objeto de conferencia
Objeto de conferencia
author Fixman, Martín
Minnoni, Martín
Sarraute, Carlos
author_facet Fixman, Martín
Minnoni, Martín
Sarraute, Carlos
author_sort Fixman, Martín
title Comparison of Feature Extraction Methods and Predictors for Income Inference
title_short Comparison of Feature Extraction Methods and Predictors for Income Inference
title_full Comparison of Feature Extraction Methods and Predictors for Income Inference
title_fullStr Comparison of Feature Extraction Methods and Predictors for Income Inference
title_full_unstemmed Comparison of Feature Extraction Methods and Predictors for Income Inference
title_sort comparison of feature extraction methods and predictors for income inference
publishDate 2017
url http://sedici.unlp.edu.ar/handle/10915/63174
http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/AGRANDA/AGRANDA-06.pdf
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AT minnonimartin comparisonoffeatureextractionmethodsandpredictorsforincomeinference
AT sarrautecarlos comparisonoffeatureextractionmethodsandpredictorsforincomeinference
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