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Open AccessArticle

Mining Individual Similarity by Assessing Interactions with Personally Significant Places from GPS Trajectories

College of Engineering, Peking University, Beijing 100871, China
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ISPRS Int. J. Geo-Inf. 2018, 7(3), 126; https://doi.org/10.3390/ijgi7030126
Received: 29 January 2018 / Revised: 16 March 2018 / Accepted: 17 March 2018 / Published: 19 March 2018
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
Human mobility is closely associated with places. Due to advancements in GPS devices and related sensor technologies, an unprecedented amount of tracking data has been generated in recent years, thus providing a new way to investigate the interactions between individuals and places, which are vital for depicting individuals’ characteristics. In this paper, we propose a framework for mining individual similarity based on long-term trajectory data. In contrast to most existing studies, which have focused on the sequential properties of individuals’ visits to public places, this paper emphasizes the essential role of the spatio-temporal interactions between individuals and their personally significant places. Specifically, rather than merely using public geographic databases, which include only public places and lack personal meanings, we attempt to interpret the semantics of places that are significant to individuals from the perspectives of personal behavior. Next, we propose a new individual similarity measurement that incorporates both the spatio-temporal and semantic properties of individuals’ visits to significant places. By experimenting on real-world GPS datasets, we demonstrate that our approach is more capable of distinguishing individuals and characterizing individual features than the previous methods. Additionally, we show that our approach can be used to effectively measure individual similarity and to aggregate individuals into meaningful subgroups. View Full-Text
Keywords: individual similarity measurement; trajectory; personally significant place; place semantics; human-place interactions individual similarity measurement; trajectory; personally significant place; place semantics; human-place interactions
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MDPI and ACS Style

Yang, M.; Cheng, C.; Chen, B. Mining Individual Similarity by Assessing Interactions with Personally Significant Places from GPS Trajectories. ISPRS Int. J. Geo-Inf. 2018, 7, 126. https://doi.org/10.3390/ijgi7030126

AMA Style

Yang M, Cheng C, Chen B. Mining Individual Similarity by Assessing Interactions with Personally Significant Places from GPS Trajectories. ISPRS International Journal of Geo-Information. 2018; 7(3):126. https://doi.org/10.3390/ijgi7030126

Chicago/Turabian Style

Yang, Mengke; Cheng, Chengqi; Chen, Bo. 2018. "Mining Individual Similarity by Assessing Interactions with Personally Significant Places from GPS Trajectories" ISPRS Int. J. Geo-Inf. 7, no. 3: 126. https://doi.org/10.3390/ijgi7030126

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