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What did you do today?: discovering daily routines from large-scale mobile data

Authors:

Katayoun Farrahi,

Daniel Gatica-PerezAuthors Info & Claims

MM '08: Proceedings of the 16th ACM international conference on Multimedia

Pages 849 - 852

https://doi.org/10.1145/1459359.1459503

Published: 26 October 2008 Publication History

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Abstract

We present a framework built from two Hierarchical Bayesian topic models to discover human location-driven routines from mobile phones. The framework uses location-driven bag representations of people's daily activities obtained from celltower connections. Using 68,000+ hours of real-life human data from the Reality Mining dataset, we successfully discover various types of routines. The first studied model, Latent Dirichlet Allocation (LDA), automatically discovers characteristic routines for all individuals in the study, including "going to work at 10am", "leaving work at night", or "staying home for the entire evening". In contrast, the second methodology with the Author Topic model (ATM) finds routines characteristic of a selected groups of users, such as "being at home in the mornings and evenings while being out in the afternoon", and ranks users by their probability of conforming to certain daily routines.

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N. Eagle and A. Pentland. "Eigenbehaviors: Identifying Structure in Routine," Behavioral Ecology and Sociobiology (in submission), 2007.

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L. Liao et al. "Location-Based Activity Recognition," Proc. NIPS, 2005.

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Qirtas MZafeiridi EPesch DWhite E(2022)Loneliness and Social Isolation Detection Using Passive Sensing Techniques: Scoping ReviewJMIR mHealth and uHealth10.2196/3463810:4(e34638)Online publication date: 12-Apr-2022
https://doi.org/10.2196/34638
Birtwistle ESchoedel RBemmann FWirth ASürig CStachl CBühner MNiklas F(2022)Mobile sensing in psychological and educational research: Examples from two application fieldsInternational Journal of Testing10.1080/15305058.2022.203616022:3-4(264-288)Online publication date: 18-Nov-2022
https://doi.org/10.1080/15305058.2022.2036160
Leiva-Araos AAllende-Cid H(2021)A Hierarchical Fuzzy-Based Correction Algorithm for the Neighboring Network Hit ProblemMathematics10.3390/math90403159:4(315)Online publication date: 5-Feb-2021
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Index Terms

What did you do today?: discovering daily routines from large-scale mobile data
1. Information systems
  1. Information retrieval

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Information & Contributors

Information

Published In

MM '08: Proceedings of the 16th ACM international conference on Multimedia

October 2008

1206 pages

ISBN:9781605583037

DOI:10.1145/1459359

General Chairs:
Abdulmotaleb EL Saddik
University of Ottawa
,
Son Vuong
University of British Colombia
,
Program Chairs:
Carsten Griwodz
University of Oslo
,
Alberto Del Bimbo
University degli Studi di Firenze
,
K. Selcuk Candan
Arizona State University
,
Alejandro Jaimes
Telefonica R&D, Madrid, Spain

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2008

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Short-paper

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MM08

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MM08: ACM Multimedia Conference 2008

October 26 - 31, 2008

British Columbia, Vancouver, Canada

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

View all

Qirtas MZafeiridi EPesch DWhite E(2022)Loneliness and Social Isolation Detection Using Passive Sensing Techniques: Scoping ReviewJMIR mHealth and uHealth10.2196/3463810:4(e34638)Online publication date: 12-Apr-2022
https://doi.org/10.2196/34638
Birtwistle ESchoedel RBemmann FWirth ASürig CStachl CBühner MNiklas F(2022)Mobile sensing in psychological and educational research: Examples from two application fieldsInternational Journal of Testing10.1080/15305058.2022.203616022:3-4(264-288)Online publication date: 18-Nov-2022
https://doi.org/10.1080/15305058.2022.2036160
Leiva-Araos AAllende-Cid H(2021)A Hierarchical Fuzzy-Based Correction Algorithm for the Neighboring Network Hit ProblemMathematics10.3390/math90403159:4(315)Online publication date: 5-Feb-2021
https://doi.org/10.3390/math9040315
Sarker IColman AHan JWatters PSarker IColman AHan JWatters P(2021)Discovering User Behavioral Rules Based on Multi-Dimensional ContextsContext-Aware Machine Learning and Mobile Data Analytics10.1007/978-3-030-88530-4_6(93-111)Online publication date: 20-Sep-2021
https://doi.org/10.1007/978-3-030-88530-4_6
Sarker IColman AHan JWatters PSarker IColman AHan JWatters P(2021)A Literature Review on Context-Aware Machine Learning and Mobile Data AnalyticsContext-Aware Machine Learning and Mobile Data Analytics10.1007/978-3-030-88530-4_3(23-56)Online publication date: 20-Sep-2021
https://doi.org/10.1007/978-3-030-88530-4_3
Feng TNarayanan S(2020)Modeling Behavioral Consistency in Large-Scale Wearable Recordings of Human Bio-Behavioral SignalsICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP40776.2020.9054493(1011-1015)Online publication date: May-2020
https://doi.org/10.1109/ICASSP40776.2020.9054493
Feng TBooth BNarayanan S(2020)Modeling Behavior as Mutual Dependency between Physiological Signals and Indoor Location in Large-Scale Wearable Sensor StudyICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP40776.2020.9054307(1016-1020)Online publication date: May-2020
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Zhang QChen JLiu X(2019)Public Perception of Haze Weather Based on Weibo CommentsInternational Journal of Environmental Research and Public Health10.3390/ijerph1623476716:23(4767)Online publication date: 28-Nov-2019
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Sarker I(2019)Context-aware rule learning from smartphone data: survey, challenges and future directionsJournal of Big Data10.1186/s40537-019-0258-46:1Online publication date: 31-Oct-2019
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Guinea ABoytsov AMouline LTraon YPoor VHan Z(2019)Smart discovery of periodic-frequent human routines for home automationProceedings of the 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services10.1145/3360774.3360784(268-277)Online publication date: 12-Nov-2019
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Discovering routines from large-scale human locations using probabilistic topic models

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