Phone call log as a context source to modeling individual user behavior

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

Research output: Book chapter/Published conference paperConference paper

17 Citations (Scopus)
4 Downloads (Pure)

Abstract

Mobile phone can record various types of context data related to a user's phone call activities in its call log. Call log provides temporal context to modeling individual user's phone call response behavior, i.e., when a user accepts, rejects or misses an incoming call. In this paper, we explore the potentiality of phone call log as a context source to modeling call response behavior of individual mobile users. Towards this, we present our initial work to generating temporal rules that capture the user's dominant call response behavior at various times of the day and days of the week, utilizing phone call log. Our preliminary experimental results on real datasets show that context information in call log can be used to model individual's phone call response behavior with high accuracy.
Original languageEnglish
Title of host publicationProceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct
Place of PublicationNew York City, NY, United States
PublisherAssociation for Computing Machinery, Inc (ACM)
Pages630-634
Number of pages5
ISBN (Electronic)9781450344623
DOIs
Publication statusPublished - 12 Sep 2016
Event2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016 - Kongresshaus Stadthalle Heidelberg, Heidelberg, Germany
Duration: 12 Sep 201616 Sep 2016
http://www.ubicomp.org/ubicomp2016/

Conference

Conference2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016
CountryGermany
CityHeidelberg
Period12/09/1616/09/16
Internet address

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  • Cite this

    Sarker, I. H., Colman, A., Kabir, M. A., & Han, J. (2016). Phone call log as a context source to modeling individual user behavior. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct (pp. 630-634). Association for Computing Machinery, Inc (ACM). https://doi.org/10.1145/2968219.2971592