Mining mobility evolution from check-in datasets

Meng Fen Chiang*, Chien Cheng Chen, Wen-Chih Peng, Philip S. Yu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The advances in location-acquisition and smart phone technologies have led to a myriad of location-based social media. Therefore, analyzing the increasing amount of spatio-temporal data emerges as an important topic. Most studies on geographic data mining focus on exploring static mobility patterns. As the amount of incoming data streams increases, revealing the temporal aspect of user mobility patterns is worth investigating. This paper targets on mining user mobility patterns over time (referred to as mobility evolution) from streams of check-in records. Intuitively, at each time slot, a mobility pattern indicates spatial regions where users stay. Therefore, given a set of time slots, mobility evolution refers a sequence of spatial regions at each time slot. Note that nearby time slots may have similar spatial region distribution. Thus, given check-in datasets, we use the idea of data compression to obtain a sequence of representative segments, where each representative segment captures spatial region distribution at the corresponding time interval. To measure the quality of a segmentation result, we propose a representation cost function based on the Minimum Description Length (MDL) principle. In addition, because deriving the sequence of segments incurs expensive computational cost, we propose a family of greedy algorithms for segmentation to serve diverse requirements: efficient compression, informative compression, and cost-effective compression. Besides, to handle the massive amount of incoming check-in data, we also propose an incremental compression approach to incrementally update the mobility evolution. We conduct experiments on Foursquare datasets to demonstrate both the effectiveness and efficiency of our proposed algorithms.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE 15th International Conference on Mobile Data Management, IEEE MDM 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages195-204
Number of pages10
ISBN (Electronic)9781479957057
DOIs
StatePublished - 5 Oct 2014
Event15th IEEE International Conference on Mobile Data Management, IEEE MDM 2014 - Brisbane, Australia
Duration: 15 Jul 201418 Jul 2014

Publication series

NameProceedings - IEEE International Conference on Mobile Data Management
Volume1
ISSN (Print)1551-6245

Conference

Conference15th IEEE International Conference on Mobile Data Management, IEEE MDM 2014
CountryAustralia
CityBrisbane
Period15/07/1418/07/14

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