Skip to content

wsgan001/discovering_user_habbits_from_smartphone_logs

 
 

Repository files navigation

master_thesis_report

Open my_thesis/main.pdf

Description of an unsupervised model developed to discover User Habits (working hours, working days, sports times, family visits, ect...) from his smartphone data. This model is a latent variable probabilistic model inspired form LDA (Latent Dirichlet Allocation).

The model was tested on a Sony smartphone dataset. The report also discusses the results of the model and shows that it outperforms current state of the art models (LDA, LCBMF).

The model was developed and tested using Python and Matlab.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • TeX 58.6%
  • Python 24.3%
  • PostScript 12.1%
  • MATLAB 3.3%
  • C 1.4%
  • Perl 0.2%
  • Other 0.1%