What's in the apps for context?
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What's in the apps for context?

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Mobile phones became multi-purpose devices supporting their users with large variety of applications for various tasks. Not only the number of available applications is increasing, also the number of ...

Mobile phones became multi-purpose devices supporting their users with large variety of applications for various tasks. Not only the number of available applications is increasing, also the number of applications people are using on their devices is growing, as well as the amount of time people spent on their smartphones daily is getting bigger. In this workshop paper, we briefly describe our past work on understanding mobile application usage. We explain our research tool for measuring mobile application usage, called AppSensor, and discuss possibilities to exploit the information of mobile application usage to inform the reasoning about users’ contexts. We contribute our source code to the workshop for a discussion and prototyping of use cases leveraging the information of which application a user is currently using.

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What's in the apps for context? What's in the apps for context? Presentation Transcript

  • What’s in the Apps for Context? Extending a Sensor for Studying App Usage to Informing Context-awareness Matthias Böhmer Christian Lander Antonio Krüger UbiMI Workshop at UbiComp 2013 September 8-9, 2013 Zürich, Switzerland
  • 1983
  • Evolution View slide
  • 4 View slide
  • AppSensor: Tracing App Usage who wherewhen how longwhich app A
  • Data from Deployment - 4,125 users from various countries - 22,626 apps from 20 categories - 4.92 million data points - 127 days 6
  • During Course of a Day - App usage correlates with circadian circle 25,000 50,000 75,000 100,000 125,000 150,000 175,000 200,000 12am 2am 4am 6am 8am 10am 12pm 2pm 4pm 6pm 8pm 10pm Applicationlaunches 7
  • Probability of Launches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igure 5. Hourly relative app usage by category in terms of launches. Each cell value refers to the percentage of app launches d within each hour for each category. Colors are normalized by row, with green indicating each category’s maximum percentage of and white indicating each category’s minimum. For example, games reach their peak in the evening (green) and trough in the morn - Type of used apps changes during the course of the day - During day: primarily communication apps - During night: scope of apps more heterogenous 8
  • Support for App Launching 9 - Adaptive launcher menu - Support visual search for apps - Presenting 5 icons for next app - Implements different models - Sequentially used apps - Prediction model - Locally most used apps - Most recently used apps - Most frequently used apps - Application AppKicker - Extension as a widget - Deployed on app store - 53,000 installations Will be presented at UbiComp 2013 Session „Systems“ Wed 8:30-10:00
  • App Recommender System 10 - Implementation of a recommender system - Context-aware (location, time and previous app) - Based on traces of application usage (AppSensor) - Application appazaar - Deployed on app store - 7,200 installations - Testbed for different recommender engines
  • Findings - Interruptions do not happen as often as expected - 8% of app use is interrupted by app switching - 3% of app use is interrupted by phone calls - If interruptions happen, overhead may be exceedingly high phone call app switch Daily interruptions (% usage) 3.2 (2.2) 8.3 (5.3) per user Regular app runtime (s) 24.8 (31.8) 18.9 (24.4) per app Overhead duration (s) 43.2 (65.9) 34.4 (40.7) per app mean (SD) 11
  • Re-Design of Phone UIs plementation ved form single-purpose devices to multi-purpose devices call applications did not evolve accordingly s can interrupt concurrent application use of call applications to allow for higher degree of multitasking one Call Applications screen modal dialogs providing only options to accept or decline call ditional third option besides accept/decline to allow user to return to previous application user to keep attention in previous application while call is pending tions: Puts incoming call into background for user to pickup call at will ompletion: Wait until task is done and display call when user leaves previous app CALLER NAME CALLER NAME b) Postponing calls c) Multiplexing d) Background notification Interruptions do not happen as often as expected - Extending the design space for phone call UIs - New interaction design for phone call handling - Support for better multitasking with call notifications - Application CallHeads deployed on app store (30,000 users) 12
  • What‘s in the apps for context?
  • tourist using city guide shopper shopping list
  • Context App Usage Matthias Böhmer matthias.boehmer@dfki.de http://matthiasboehmer.de