Split menus: effectively using selection frequency to organize menus
ACM Transactions on Computer-Human Interaction (TOCHI)
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
IEEE Pervasive Computing
Inducing shortcuts on a mobile phone interface
Proceedings of the 11th international conference on Intelligent user interfaces
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Learning Bayesian Networks
MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones
Proceedings of the 5th international conference on Mobile systems, applications and services
Contextual patterns in mobile service usage
Personal and Ubiquitous Computing
Landmark detection from mobile life log using a modular Bayesian network model
Expert Systems with Applications: An International Journal
Operation Prediction for Context-Aware User Interfaces of Mobile Phones
SAINT '09 Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet
Automatic mobile menu customization based on user operation history
Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services
SmartActions: Context-Aware Mobile Phone Shortcuts
INTERACT '09 Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I
Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services
Proceedings of the 2013 international conference on Intelligent user interfaces
Prefetching mobile ads: can advertising systems afford it?
Proceedings of the 8th ACM European Conference on Computer Systems
A study on icon arrangement by smartphone users
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Bezel-Tap gestures: quick activation of commands from sleep mode on tablets
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Oh app, where art thou?: on app launching habits of smartphone users
Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services
Practical prediction and prefetch for faster access to applications on mobile phones
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Prophet: what app you wish to use next
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Proceedings of the 2013 International Symposium on Wearable Computers
On mining mobile apps usage behavior for predicting apps usage in smartphones
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
Capturing mobile experience in the wild: a tale of two apps
Proceedings of the ninth ACM conference on Emerging networking experiments and technologies
Less is more: classifying mobile interactions to support context sensing in journeys
BCS-HCI '13 Proceedings of the 27th International BCS Human Computer Interaction Conference
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It is becoming harder to find an app on one's smart phone due to the increasing number of apps available and installed on smart phones today. We collect sensory data including app use from smart phones, to perform a comprehensive analysis of the context related to mobile app use, and build prediction models that calculate the probability of an app in the current context. Based on these models, we developed a dynamic home screen application that presents icons for the most probable apps on the main screen of the phone and highlights the most probable one. Our models outperformed other strategies, and, in particular, improved prediction accuracy by 8% over Most Frequently Used from 79.8% to 87.8% (for 9 candidate apps). Also, we found that the dynamic home screen improved accessibility to apps on the phone, compared to the conventional static home screen in terms of accuracy, required touch input and app selection time.