Mining semantic sequential patterns from geo-tagged photos

Cai, Guochen, Lee, Kyungmi, and Lee, Ickjai (2016) Mining semantic sequential patterns from geo-tagged photos. In: Proceedings of the 49th Hawaii International Conference on System Sciences. 1379. pp. 2187-2196. From: HICSS 2016: 49th Hawaii International Conference on System Sciences, 5-8 January 2016, Koloa, HI, USA.

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Social media data associated with geographic location and time information reflect people footprint in real world. Abundance of geo-referenced content represents a massive opportunity to understanding of human geographic mobility behaviors. Most trajectory mining research from geo-enabled social media data focus on spatial geometric features. Integrating trajectory analysis with semantic information can implicate human movement behaviors on semantic levels. In this work, we illustrate a study on mining semantically enriched trajectory patterns using geo-referenced content especially using geo-tagged photo data for case study. We first propose a semantic region of interest mining technique to extract reference regions with semantic information. We then present a multi-dimensional sequential pattern mining algorithm to find trajectory patterns with various semantic dimension combinations. We apply our method to real geo-tagged photo data to discover interesting patterns about sequential movement related to multiple semantics. Experimental results show that our method is able to find useful semantic trajectory patterns from geo-tagged content and deal with multi-dimensional semantic trajectories.

Item ID: 47544
Item Type: Conference Item (Research - E1)
ISBN: 978-0-7695-5670-3
Keywords: semantics, trajectory, data mining, media, feature extraction, Australia,spatio-temporal, trajectory, data mining, semantic
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Date Deposited: 07 Mar 2017 00:59
FoR Codes: 46 INFORMATION AND COMPUTING SCIENCES > 4605 Data management and data science > 460502 Data mining and knowledge discovery @ 100%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890202 Application Tools and System Utilities @ 100%
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