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Automatic mobile menu customization based on user operation history

Published: 15 September 2009 Publication History

Abstract

Mobile devices are becoming more and more difficult to use due to the sheer number of functions now supported. In this paper, we propose a menu customization system that ranks functions so as to make interesting functions, both frequently used functions and rarely used functions, easy to access. Concretely, we define the features of phone functions by extracting keywords from the manufacturer's manual, and propose the method that ranks the functions based on user operation history by using Ranking SVM (Support Vector Machine). We conduct a home-use test for one week to evaluate the efficiency of customization and the usability of menu customization. The results show that the average rank of used functions on the last day of the test is half of that of first day and almost 70 % of the users are satisfied with the ranking provided by menu customization and the usability of menus. In addition, interviews show that automatic mobile menu customization is more appropriate for mobile phone beginner rather than the master users.

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  • (2019)Exploring a Design Space of Graphical Adaptive MenusACM Transactions on Interactive Intelligent Systems10.1145/323719010:1(1-40)Online publication date: 29-Jul-2019
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MobileHCI '09: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services
September 2009
473 pages
ISBN:9781605582818
DOI:10.1145/1613858

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 September 2009

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Author Tags

  1. SVM
  2. mobile menu
  3. personalization
  4. recommendation
  5. support vector machine

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MobileHCI '09

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MobileHCI '09 Paper Acceptance Rate 23 of 95 submissions, 24%;
Overall Acceptance Rate 202 of 906 submissions, 22%

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  • (2020)Presentation System of Operating Histories to Support Choice and Operation of Tools for Beginners of Text Mining Software TETDMTETDMを用いたテキストマイニング初心者のツールの選択と操作を助ける操作履歴の提示Journal of Japan Society for Fuzzy Theory and Intelligent Informatics10.3156/jsoft.32.5_84132:5(841-850)Online publication date: 15-Oct-2020
  • (2020)A Framework to Decide Adaptive Functionalities by Considering User Emotions and the Context2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer)10.1109/ICTer51097.2020.9325497(178-183)Online publication date: 4-Nov-2020
  • (2019)Exploring a Design Space of Graphical Adaptive MenusACM Transactions on Interactive Intelligent Systems10.1145/323719010:1(1-40)Online publication date: 29-Jul-2019
  • (2019)Click Sequence Prediction in Android Mobile ApplicationsIEEE Transactions on Human-Machine Systems10.1109/THMS.2018.286880649:3(278-289)Online publication date: Jun-2019
  • (2019)G-Menu: A Keyword-by-Gesture Based Dynamic Menu Interface for SmartphonesHuman-Computer Interaction. Recognition and Interaction Technologies10.1007/978-3-030-22643-5_8(99-114)Online publication date: 27-Jun-2019
  • (2018)A Framework for Interaction-driven User Modeling of Mobile News Reading BehaviourProceedings of the 26th Conference on User Modeling, Adaptation and Personalization10.1145/3209219.3209229(33-41)Online publication date: 3-Jul-2018
  • (2018)Cloud MenusProceedings of the 23rd International Conference on Intelligent User Interfaces10.1145/3172944.3172975(317-328)Online publication date: 5-Mar-2018
  • (2016)A novel approach to improve the planning of adaptive and interactive sessions for the treatment of Major DepressionInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2015.11.00387:C(80-91)Online publication date: 1-Mar-2016
  • (2014)ReflectionProceedings of the 27th annual ACM symposium on User interface software and technology10.1145/2642918.2647355(689-698)Online publication date: 5-Oct-2014
  • (2014)Predictive, adaptive mobile user interfacesProceedings of the 2014 ACM Southeast Conference10.1145/2638404.2638502(1-3)Online publication date: 28-Mar-2014
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