Sequences of purchases in credit card data reveal lifestyles in urban populations

@article{DiClemente2018SequencesOP,
  title={Sequences of purchases in credit card data reveal lifestyles in urban populations},
  author={Riccardo Di Clemente and Miguel Luengo-Oroz and Mat{\'i}as Travizano and Sharon C. Xu and Bapu Vaitla and Marta C. Gonz{\'a}lez},
  journal={Nature Communications},
  year={2018},
  volume={9}
}
Zipf-like distributions characterize a wide set of phenomena in physics, biology, economics, and social sciences. In human activities, Zipf's law describes, for example, the frequency of appearance of words in a text or the purchase types in shopping patterns. In the latter, the uneven distribution of transaction types is bound with the temporal sequences of purchases of individual choices. In this work, we define a framework using a text compression technique on the sequences of credit card… 

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