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Author (up) Campo-Vázquez, C.; García-Rubio, C.; Rodriguez-Carrion, A.; Das, S. url  doi
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  Title Analysis of a fast LZ-based entropy estimator for mobility data Type Conference Article
  Year 2015 Publication 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops) Abbreviated Journal  
  Volume Issue Pages 451-456  
  Keywords emrisco, entropy, lz, mobility data  
  Abstract Randomness in people’s movements might serve to detect behavior anomalies. The concept of entropy can be used for this purpose, but its estimation is computational intensive, particularly when processing long movement histories. Moreover, disclosing such histories to third parties may violate user privacy. With a goal to keep the mobility data in the mobile device itself yet being able to measure randomness, we propose three fast entropy estimators based on Lempel-Ziv (LZ) prediction algorithms. We evaluated them with 95 movement histories of real users tracked during 9 months using GSM-based mobility data. The results show that the entropy tendencies of the approaches proposed in this work and those in the literature are the same as time evolves. Therefore, our proposed approach could potentially detect variations in the mobility patterns of the user with a lower computational cost. This allows to unveil shifts in the users mobility behavior without disclosing their sensible location data.  
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  Corporate Author Thesis  
  Publisher IEEE Publishing Services Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-4799-8425-1 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number UC3M @ josealga @ campo017 Serial 63  
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