Williams, Matthew J., Whitaker, Roger M. ORCID: https://orcid.org/0000-0002-8473-1913 and Allen, Stuart M. ORCID: https://orcid.org/0000-0003-1776-7489 2017. There and back again: detecting regularity in human encounter communities. IEEE Transactions on Mobile Computing 16 (6) , pp. 1744-1757. 10.1109/TMC.2016.2599169 |
Preview |
PDF
- Accepted Post-Print Version
Download (1MB) | Preview |
Abstract
Detecting communities that recur over time is a challenging problem due to the potential sparsity of encounter events at an individual scale and inherent uncertainty in human behavior. Existing methods for community detection in mobile human encounter networks ignore the presence of temporal patterns that lead to periodic components in the network. Daily and weekly routine are prevalent in human behavior and can serve as rich context for applications that rely on person-to-person encounters, such as mobile routing protocols and intelligent digital personal assistants. In this article, we present the design, implementation, and evaluation of an approach to decentralized periodic community detection that is robust to uncertainty and computationally efficient. This alternative approach has a novel periodicity detection method inspired by a neural synchrony measure used in the field of neurophysiology. We evaluate our approach and investigate human periodic encounter patterns using empirical datasets of inferred and direct-sensed encounters.
Item Type: | Article |
---|---|
Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Publisher: | IEEE |
ISSN: | 1536-1233 |
Funders: | EC |
Date of First Compliant Deposit: | 26 September 2016 |
Date of Acceptance: | 20 July 2016 |
Last Modified: | 17 Nov 2024 07:45 |
URI: | https://orca.cardiff.ac.uk/id/eprint/94922 |
Citation Data
Cited 5 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
Edit Item |