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

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

doi:10.1145/2968219.2971592

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 paper › Conference paper › peer-review

19 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 language	English
Title of host publication	Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct
Place of Publication	New York City, NY, United States
Publisher	Association for Computing Machinery, Inc (ACM)
Pages	630-634
Number of pages	5
ISBN (Electronic)	9781450344623
DOIs	https://doi.org/10.1145/2968219.2971592
Publication status	Published - 12 Sep 2016
Event	2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016 - Kongresshaus Stadthalle Heidelberg, Heidelberg, Germany Duration: 12 Sep 2016 → 16 Sep 2016 http://www.ubicomp.org/ubicomp2016/

Conference

Conference	2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016
Country/Territory	Germany
City	Heidelberg
Period	12/09/16 → 16/09/16
Internet address	http://www.ubicomp.org/ubicomp2016/

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10.1145/2968219.2971592

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@inproceedings{8db46af19d4e463987771d4b29883490,

title = "Phone call log as a context source to modeling individual user behavior",

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.",

keywords = "Call Log, Mobile Phone, Rule Discovery, Temporal Context, User Behavior Modeling",

author = "Sarker, {Iqbal H.} and Alan Colman and Kabir, {Muhammad Ashad} and Jun Han",

year = "2016",

month = sep,

day = "12",

doi = "10.1145/2968219.2971592",

language = "English",

pages = "630--634",

booktitle = "Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct",

publisher = "Association for Computing Machinery, Inc (ACM)",

note = "2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016 ; Conference date: 12-09-2016 Through 16-09-2016",

url = "http://www.ubicomp.org/ubicomp2016/",

}

Sarker, IH, Colman, A, Kabir, MA & 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. Association for Computing Machinery, Inc (ACM), New York City, NY, United States, pp. 630-634, 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016, Heidelberg, Germany, 12/09/16. https://doi.org/10.1145/2968219.2971592

Phone call log as a context source to modeling individual user behavior. / Sarker, Iqbal H.; Colman, Alan; Kabir, Muhammad Ashad; Han, Jun.

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct. New York City, NY, United States : Association for Computing Machinery, Inc (ACM), 2016. p. 630-634.

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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AU - Sarker, Iqbal H.

AU - Colman, Alan

AU - Kabir, Muhammad Ashad

AU - Han, Jun

PY - 2016/9/12

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N2 - 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.

AB - 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.

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

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