HCFContext: Smartphone context inference via sequential history-based collaborative filtering

Vidyasagar Sadhu, Saman Zonouz, Vincent Sritapan, Dario Pompili

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Mobile context determination is an important step for many context-aware services such as location-based services, enterprise policy enforcement, building/room occupancy detection for power/HVAC operation, etc. Especially in enterprise scenarios where policies (e.g., attending a confidential meeting only when the user is in "Location X") are defined based on mobile context, it is paramount to verify the accuracy of the mobile context. To this end, two stochastic models based on the theory of Hidden Markov Models (HMMs) to obtain mobile context are proposed - personalized model (HPContext) and collaborative filtering model (HCFContext). The former predicts the current context using sequential history of the user's past context observations; the latter enhances HPContext with collaborative filtering features, which enables it to predict the current context of the primary user based on the context observations of users related to the primary user, e.g., same team colleagues in company, gym friends, family members, etc. Each of the proposed models can also be used to enhance/complement the context obtained from sensors. Furthermore, since privacy is a concern in collaborative filtering, a privacy-preserving method is proposed to derive HCFContext model parameters based on the concepts of homomorphic encryption. Finally, these models are thoroughly validated on a real-life dataset.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Pervasive Computing and Communications, PerCom 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538691489
DOIs
StatePublished - Mar 2019
Event2019 IEEE International Conference on Pervasive Computing and Communications, PerCom 2019 - Kyoto, Japan
Duration: Mar 12 2019Mar 14 2019

Publication series

Name2019 IEEE International Conference on Pervasive Computing and Communications, PerCom 2019

Conference

Conference2019 IEEE International Conference on Pervasive Computing and Communications, PerCom 2019
Country/TerritoryJapan
CityKyoto
Period3/12/193/14/19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Media Technology
  • Computer Science Applications

Keywords

  • Collaborative filtering
  • Location
  • Mobile context
  • Personalized model
  • Prediction
  • Privacy-preserving
  • Sensors

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