Noise Reduction of Mobile Sensors Data in the Prediction of Demographic Attributes

Itay Hazan, Asaf Shabtai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In this paper we attempt demonstrate how we can use smartphone sensor data effectively for predicting gender. We specifically focus on sensor data that is assumed to inflict minimal risk to other applications, the system, or the user: Installed Applications, Network Traffic Amount, and Accelerometer readings. We propose several simple heuristics for pre-processing the data and for noise reduction which eventually results in improved accuracy in predicting gender.

Original languageEnglish
Title of host publicationProceedings - 2nd ACM International Conference on Mobile Software Engineering and Systems, MOBILESoft 2015
PublisherInstitute of Electrical and Electronics Engineers
Pages117-120
Number of pages4
ISBN (Electronic)9781479919345
DOIs
StatePublished - 28 Sep 2015
Event2nd ACM International Conference on Mobile Software Engineering and Systems, MOBILESoft 2015 - Florence, Italy
Duration: 16 May 201517 May 2015

Publication series

NameProceedings - 2nd ACM International Conference on Mobile Software Engineering and Systems, MOBILESoft 2015

Conference

Conference2nd ACM International Conference on Mobile Software Engineering and Systems, MOBILESoft 2015
Country/TerritoryItaly
CityFlorence
Period16/05/1517/05/15

Keywords

  • Demographic Prediction
  • Smartphone

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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