Contexto: Lessons learned from mobile context inference

Moshe Unger, Ariel Bar, Bracha Shapira, Lior Rokach, Ehud Gudes

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

5 Scopus citations

Abstract

Context-aware computing aims at tailoring services to the user's circumstances and surroundings. Our study examines how data collected from mobile devices can be utilized to infer users' behavior and environment. We present the results and the lessons learned from a two-week user study of 40 students. The data collection was performed using Contexto, a framework for collecting data from a rich set of sensors installed on mobile devices, which was developed for this purpose. We studied various new and fine-grained user contexts which are relevant to students' daily activities, such as "in class and interested in the learned materials" and "on my way to campus". These contexts might later be utilized for various purposes such as recommending relevant items to the students' context. We compare various machine learning methods and report their effectiveness for the purposes of inferring the users' context from the collected data. In addition, we present our findings on how to evaluate context inference systems, on the importance of explicit and latent labeling for context inference and on the effect of new users on the results' accuracy.

Original languageEnglish
Title of host publicationUbiComp 2014 - Adjunct Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PublisherAssociation for Computing Machinery, Inc
Pages175-178
Number of pages4
ISBN (Electronic)9781450330473
DOIs
StatePublished - 1 Jan 2014
Event2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014 - Seattle, United States
Duration: 13 Sep 201417 Sep 2014

Publication series

NameUbiComp 2014 - Adjunct Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Conference

Conference2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014
Country/TerritoryUnited States
CitySeattle
Period13/09/1417/09/14

Keywords

  • Context-aware
  • Inference
  • Machine learning
  • Mobile sensors

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