Evidence-based behavioral model for calendar schedules of individual mobile phone users

Iqbal H. Sarker, Muhammad Ashad Kabir, Alan Colman, Jun Han

Research output: Book chapter/Published conference paperConference paperpeer-review

9 Citations (Scopus)


The electronic calendar usually serves as a personal organizer and is a valuable resource for managing daily activities or schedules of the users. Naturally, a calendar provides various contextual information about individual's scheduled events/appointments, e.g., meeting. A number of researchers have utilized such information to predict human behavior for mobile communication, by assuming a predefined event-behavior mapping which is static and non-personalized. However, in the real world, people differ from each other in how they respond to incoming calls during their scheduled events, even a particular individual may respond differently subject to what type of event is scheduled in the calendar. Thus a static behavioral model does not necessarily map to calendar schedules and corresponding phone call response behavior of individuals. Therefore, we propose an evidence based behavioral model (EBM) that dynamically identifies the actual call response behavior of individuals for various calendar events based on their mobile phone log that records the data related to a user's phone call activities. Experiments on real datasets show that our proposed technique better captures the user's call response behavior for various calendar events, thereby enabling more appropriate rules to be created for the purpose of automated handling of incoming calls in an intelligent call interruption management system.
Original languageEnglish
Title of host publicationProceedings of the 3rd IEEE international conference on data science and advanced analytics
Subtitle of host publicationDSAA 2016
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages10
ISBN (Electronic)9781509052066
ISBN (Print)9781509052073 (Print on demand)
Publication statusPublished - 2016
EventIEEE DSAA 2016: 3rd IEEE International Conference on Data Science and Advanced Analytics - Montreal Marriott Chateau Champlain, Montréal, Canada
Duration: 17 Oct 201619 Oct 2016
https://sites.ualberta.ca/~dsaa16/ (Conference website)
https://sites.ualberta.ca/~dsaa16/docs/IEEE-DSAA2016-announce2.pdf (Conference brochure)


ConferenceIEEE DSAA 2016
OtherFollowing the first successful edition DSAA'2014 held in 2014 in Shanghai, then the second successful edition DSAA'2015 held in Paris, the 2016 IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA'2016), sponsored by the IEEE Computational Intelligence Society, aims to provide a premier forum that brings together researchers, industry practitioners, as well as potential users of big data, for discussion and exchange of ideas on the latest theoretical developments in Data Science as well as on the best practices for a wide range of applications.

IEEE DSAA'2016 will consist of two main Tracks: Research and Application; the Research Track is aimed at collecting contributions related to theoretical foundations of Data Science and Data Analytics. The Application Track is aimed at collecting contributions related to applications of Data Science and Data Analytics in real life scenarios. DSAA solicits then both theoretical and practical works on data science and advanced analytics.
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