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Prediction of Socioeconomic Levels using Cell Phone Records V. Soto, V. Frias-Martinez, J. Virseda and E. Frias-Martinez Telefonica Research, Madrid, Spain {vsoto,vanessa,jvirseda,efm}@tid.es
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Document Date: 2018-07-13 17:06:20

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File Size: 397,40 KB

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City

Madrid / /

Company

Weka Data Mining Software / Telefonica / /

Country

Spain / /

/

Facility

BTS tower / National Statistical Institute / BTS towers / /

IndustryTerm

residential location algorithm / grid search / potential applications / electricity / cell phone networks / compromise solution / public transportation / social networks / large online social communities / pre-processing / basic services / line algorithm / cell phone devices / /

MarketIndex

set 1200 / /

NaturalFeature

Random Forest Random Forest / Random forest / SVMs forest / /

Organization

National Statistical Institute / /

Person

Records V. Soto / V / /

Product

SVMs / using SVMs / /

ProgrammingLanguage

Java / /

Technology

cellular telephone / SMS / line algorithm / scanning algorithm / Java / residential location algorithm / cell phones / machine learning / implemented using the SVM library libsvm-Java / /

URL

http /

SocialTag