Behavior-Oriented Time Segmentation for Mining Individualized Rules of Mobile Phone Users

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

Research output: Book chapter/Published conference paperConference paper

11 Citations (Scopus)

Abstract

Mobile or cellular phones can record various types of context data related to a user's phone call activities. In this paper, we present an approach to discovering individualized behavior rules for mobile users from their phone call records, based on the temporal context in which a user accepts, rejects or misses a call. One of the determinants of an individual's phone behavior is the various activities undertaken at various times of a day and days of the week. In many cases, such behavior will follow temporal patterns. Currently, researchers modeling user behavior using temporal context statically segment time into arbitrary categories (e.g., morning, evening) or periods (e.g., 1 hour). However, such time categorization does not necessarily map to the patterns of individual user activity and subsequent behavior. Therefore, we propose a behavior-oriented time segmentation (BOTS) technique that dynamically identifies diverse time segments for an individual user's behaviors based on the phone call records. Experiments on real datasets show that our proposed technique better captures the user's dominant call response behavior at various times of the day and week, 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 publicationIEEE International Conference on Data Science and Advanced Analytics, DSAA 2016, Montreal, QC, Canada, October 17-19, 2016
Place of PublicationUnited States
PublisherIEEE
Pages488-497
Number of pages10
ISBN (Electronic)9781509052066
ISBN (Print)9781509052073
DOIs
Publication statusPublished - 2016
EventIEEE International Conference on Data Science and Advanced Analytics (DSAA 2016) - Montreal Marriott Chateau Champlain, Montréal, Canada
Duration: 16 Oct 201618 Oct 2016
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7796877

Conference

ConferenceIEEE International Conference on Data Science and Advanced Analytics (DSAA 2016)
CountryCanada
CityMontréal
Period16/10/1618/10/16
Internet address

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    Sarker, I. H., Colman, A., Kabir, M. A., & Han, J. (2016). Behavior-Oriented Time Segmentation for Mining Individualized Rules of Mobile Phone Users. In IEEE International Conference on Data Science and Advanced Analytics, DSAA 2016, Montreal, QC, Canada, October 17-19, 2016 (pp. 488-497). IEEE. https://doi.org/10.1109/DSAA.2016.60