Due to the popularity of context-aware computing and the rapid growth of the smart phone devices, modeling an individual's phone call response behavior may assist them in their daily activities for managing call interruptions. A key step of such modeling is to discovering call response behavioral rules based on multi-dimensional contexts related to individual's behavior. Currently, researchers use classification rule learners for modeling individual's mobile phone behavior. However, the problem is that such learning techniques produce only rules that include maximal number of contexts albeit ordered by relevance. This results in many rules with low-reliability that decrease the accuracy of the modeling approach. In this paper, we propose an approach (Tmodel) to modeling individual's phone call response behavior utilizing mobile phone data. This approach produces not only general rules that capture individual's behavior at a particular level of confidence with a minimal number of contexts, but also produce rules that express specific exceptions to the general rules when more context-dimensions are taken into account. Experimental evaluation shows that our approach outperforms existing approaches to modelling individual's phone call response behavior based on multidimensional contexts.
|Title of host publication||Proceedings of the 2017 IEEE/ACM 4th International Conference on Mobile Software Engineering and Systems (MOBILESoft 2017)|
|Place of Publication||United States|
|Publisher||IEEE, Institute of Electrical and Electronics Engineers|
|Number of pages||5|
|Publication status||Published - 11 Jul 2017|
|Event||4th IEEE/ACM International Conference on Mobile Software Engineering and Systems: MOBILESoft 2017 - Pontificia Universidad Católica Argentina (UCA), Buenos Aires, Argentina|
Duration: 22 May 2017 → 23 May 2017
http://mobilesoftconf.org/2017/ (Conference website)
https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7961439 (Conference proceedings)
|Conference||4th IEEE/ACM International Conference on Mobile Software Engineering and Systems|
|Period||22/05/17 → 23/05/17|
|Other||In recent years, the massive increase in the use of mobile applications has greatly influenced the way people go about their daily life. The number of available mobile applications has grown enormously since the establishment of app stores and marketplaces that enable users to download and seamlessly install apps. Mobile platforms are rapidly changing and include diverse capabilities such as GPS, cameras, several wireless communications (WLAN, 4G, RFID etc), a variety of on-device memory and disk capacities, and various sensors.|
Innovative mobile services and exciting mobile applications are emerging as a result of the ingenious use of these technologies. Consequently, the development of mobile applications has also been growing at a fast pace, presenting new challenges to Software Engineering. Developing versatile and robust mobile applications requires formally grounded methods, as well as advanced practices and tools.
MOBILESoft provides a working conference-style forum for the discussion and presentation of innovative contributions to the research and practice of the design, development, validation, execution, and evolution of mobile applications.
Sarker, I. H., Kabir, M. A., Colman, A., & Han, J. (2017). An Approach to Modeling Call Response Behavior on Mobile Phones Based on Multi-Dimensional Contexts. In Proceedings of the 2017 IEEE/ACM 4th International Conference on Mobile Software Engineering and Systems (MOBILESoft 2017) (pp. 91-95).  IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/MOBILESoft.2017.38