Identifying Recent Behavioral Data Length in Mobile Phone Log

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

14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

Research Article

Identifying Recent Behavioral Data Length in Mobile Phone Log

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/eai.7-11-2017.2275019,
    author={Iqbal Sarker and Muhammad Ashad Kabir and Alan Colman and Jun Han},
    title={Identifying Recent Behavioral Data Length in Mobile Phone Log},
    proceedings={14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services},
    publisher={ACM},
    proceedings_a={MOBIQUITOUS},
    year={2018},
    month={4},
    keywords={mobile data mining behavior modeling contexts recency},
    doi={10.4108/eai.7-11-2017.2275019}
}

Iqbal Sarker
Muhammad Ashad Kabir
Alan Colman
Jun Han
Year: 2018
Identifying Recent Behavioral Data Length in Mobile Phone Log
MOBIQUITOUS
ACM
DOI: 10.4108/eai.7-11-2017.2275019

Iqbal Sarker¹^,*, Muhammad Ashad Kabir², Alan Colman¹, Jun Han¹

1: Swinburne University of Technology
2: Charles Sturt University

*Contact email: iqbal.sarker.cse@gmail.com

Abstract

Mobile phone log data (e.g., phone call log) is not static as it is progressively added to day-by-day according to individual's diverse behaviors with mobile phones. Since human behavior changes over time, the most recent pattern is more interesting and significant than older ones for predicting individual's behavior. The goal of this poster paper is to identify the recent behavioral data length dynamically from the entire phone log for recency-based behavior modeling. To the best of our knowledge, this is the rst dynamic recent log-based study that takes into account individual's recent behavioral patterns for modeling their phone call behaviors.

Keywords: mobile data mining behavior modeling contexts recency

Published: 2018-04-18
Publisher: ACM

: http://dx.doi.org/10.4108/eai.7-11-2017.2275019