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Constructing semantic interpretation of routine and anomalous mobility behaviors from big data

Georg Fuchs, Hendrik Stange, Dirk Hecker, Natalia Andrienko, Gennady Andrienko
2015 SIGSPATIAL Special  
Temporal patterns of people's presence in the places resulted from spatio-temporal aggregation of the data by the places and hourly intervals within the weekly cycle.  ...  Repeatedly visited personal and public places were extracted from trajectories by finding spatial clusters of stop points.  ...  A common pattern of development in mobility analytics is the paradigm shift from syntactic [9] to semantic [11] analysis of movement data.  ... 
doi:10.1145/2782759.2782765 fatcat:wqdenf47pbdkpfu6u6fttor43u

Towards Privacy-Preserving Semantic Mobility Analysis [article]

N. Andrienko, G. Andrienko, G. Fuchs
2013 International EuroVis Workshop on Visual Analytics  
approach based on transformation of the spatial component of movement data from the geographic space to an abstract semantic space, inspired by the concept of cartographic chorems.  ...  By analyzing data reflecting human mobility, one can derive patterns and knowledge that are tightly linked to the underlying geography and therefore cannot be applied to another territory or even compared  ...  Analysis focusing on space To analyze the temporal patterns of person's activities, which are reflected in person's presence in different semantic places, we compute the presence counts in each semantic  ... 
doi:10.2312/pe.eurovast.eurova13.019-023 dblp:conf/eurova-ws/AndrienkoAF13 fatcat:5pceo6bqjngbjammr3lfchrxye

Analysis of mobility behaviors in geographic and semantic spaces

Natalia Andrienko, Gennady Andrienko, Georg Fuchs
2014 2014 IEEE Conference on Visual Analytics Science and Technology (VAST)  
Temporal patterns of people's presence in the places resulted from spatiotemporal aggregation of the data by the places and hourly intervals within the weekly cycle.  ...  ABSTRACT Repeatedly visited personal and public places were extracted from trajectories by finding spatial clusters of stop points.  ...  EXTRACTION AND INTERPRETATION OF PLACES We used an automated tool that extracts repeatedly visited personal and public places by spatial clustering of points from trajectories.  ... 
doi:10.1109/vast.2014.7042556 dblp:conf/ieeevast/AndrienkoAF14 fatcat:jmn7cvkmonh73loa7qwflk6qpy

Interactive Visual Discovering of Movement Patterns from Sparsely Sampled Geo-tagged Social Media Data

Siming Chen, Xiaoru Yuan, Zhenhuang Wang, Cong Guo, Jie Liang, Zuchao Wang, Xiaolong Luke Zhang, Jiawan Zhang
2016 IEEE Transactions on Visualization and Computer Graphics  
By iteratively analyzing filtered movements, users can explore the semantics of movements, including the transportation methods, frequent visiting sequences and keyword descriptions.  ...  In contrast to traditional movement data, the sparseness and irregularity of social media data increase the difficulty of extracting movement patterns.  ...  This work is also supported by PKU-Qihu Joint Data Visual Analytics Research Center.  ... 
doi:10.1109/tvcg.2015.2467619 pmid:26340781 fatcat:yresa7zjunb3pgp7qquk5zibsu

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

Mengke Yang, Chengqi Cheng, Bo Chen
2018 ISPRS International Journal of Geo-Information  
Next, we propose a new individual similarity measurement that incorporates both the spatio-temporal and semantic properties of individuals' visits to significant places.  ...  individuals from the perspectives of personal behavior.  ...  Conflicts of Interest: The authors declare that they have no conflicts of interest to disclose.  ... 
doi:10.3390/ijgi7030126 fatcat:5yebgfl3ozd7jmriuvzbcdpdmi

Visual Analysis of Movement Behavior Using Web Data for Context Enrichment

Robert Krueger, Dennis Thom, Thomas Ertl
2014 2014 IEEE Pacific Visualization Symposium  
of interest) and degree of uncertainty by varying color intensity of the icons; bottom) Temporal View -showing frequent temporal daily patterns.  ...  Using a density-based clustering technique we extract 1.215 frequent destinations of ∼150.000 user movements from a large e-mobility database.  ...  The electric scooter data was kindly provided by EnBW Energie Baden-Württemberg AG. We would like to thank them for their collaboration.  ... 
doi:10.1109/pacificvis.2014.57 dblp:conf/apvis/KrugerTE14 fatcat:ryvpmznmhfbinba4lshzeag4bi

Visual Analytics Methodology for Scalable and Privacy-Respectful Discovery of Place Semantics from Episodic Mobility Data [chapter]

Natalia Andrienko, Gennady Andrienko, Georg Fuchs, Piotr Jankowski
2015 Lecture Notes in Computer Science  
Availability of personal traces over a long time period makes it possible to detect repeatedly visited places and identify them as home, work, place of social activities, etc. based on temporal patterns  ...  The semantically abstracted data can be further analyzed without the risk of re-identifying people based on the specific places they attend.  ...  Apply movement analysis methods to the semantic space trajectories. For place extraction, we have developed a special algorithm that groups position records by spatial proximity.  ... 
doi:10.1007/978-3-319-23461-8_25 fatcat:r4nhmxnumbfbxm4aqz3kze6zva

Modeling of Human Movement Behavioral Knowledge from GPS Traces for Categorizing Mobile Users

Shreya Ghosh, Soumya K. Ghosh
2017 Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion  
In this work, we present a framework which models user movement patterns containing both spatio-temporal and semantic information, generates semantic stay-point taxonomy by analysing GPS traces of all  ...  users, summarizes individuals' GPS traces and clusters users based on the semantics of their movement patterns.  ...  We propose a framework to model individuals' movement patterns, analyzing human movement patterns both from semantic and spatio-temporal context and extracting implicit information.  ... 
doi:10.1145/3041021.3054150 dblp:conf/www/GhoshG17 fatcat:cvmc4x7v5ng7loamf6adlqj2pe

A survey on next location prediction techniques, applications, and challenges

Ayele Gobezie Chekol, Marta Sintayehu Fufa
2022 EURASIP Journal on Wireless Communications and Networking  
Heterogeneous data generated from different sources, users' random movement behavior, and the time sensitivity of trajectory data are some of the challenges.  ...  It is challenging to analyze and mine trajectory data due to the complex characteristics reflected in human mobility, which is affected by multiple contextual information.  ...  Semantic trajectory Ying et al. proposed integrating semantic information about the places visited by individuals in addition to their location data in order to enhance prediction accuracy about future  ... 
doi:10.1186/s13638-022-02114-6 fatcat:s2ixs3ftibaobighbik6ikgfce

Semantic trajectories modeling and analysis

Christine Parent, Nikos Pelekis, Yannis Theodoridis, Zhixian Yan, Stefano Spaccapietra, Chiara Renso, Gennady Andrienko, Natalia Andrienko, Vania Bogorny, Maria Luisa Damiani, Aris Gkoulalas-Divanis, Jose Macedo
2013 ACM Computing Surveys  
trajectories from movement tracks, (ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and (iii) using data mining to analyze semantic trajectories  ...  In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application.  ...  Behaviors extracted from semantic trajectories cannot be obtained from raw data only.  ... 
doi:10.1145/2501654.2501656 fatcat:g7nr36bop5eslcfmr4z34mvj4i

Location prediction on trajectory data: A review

Ruizhi Wu, Guangchun Luo, Junming Shao, Ling Tian, Chengzong Peng
2018 Big Data Mining and Analytics  
Then, we review existing location-prediction methods, ranging from temporal-pattern-based prediction to spatiotemporal-pattern-based prediction.  ...  First, we introduce the types of trajectory data and related basic concepts.  ...  This research was supported by the Foundation of Science & Technology Department of Sichuan Province (Nos. 2017JY0027 and 2016GZ0075), the National Key Research and Development Program (2016YFB0502300)  ... 
doi:10.26599/bdma.2018.9020010 dblp:journals/bigdatama/WuLSTP18 fatcat:3ogap5xsxffjxazjm7chcnqu3u

Where Chicagoans tweet the most: Semantic analysis of preferential return locations of Twitter users [article]

Aiman Soliman, Junjun Yin, Kiumars Soltani, Anand Padmanabhan and Shaowen Wang
2015 arXiv   pre-print
In this connection, the movements of Twitter users captured by geo-located tweets were found to follow similar patterns, where a few geographic locations dominate the tweeting activity of individual users  ...  Top-visited locations were identified by clustering semantic enriched tweets using a DBSCAN algorithm.  ...  Insightful comments were received from members of the CyberGIS Center for Advanced Digital and Spatial Studies. 6.  ... 
arXiv:1512.06880v1 fatcat:lgkbxlwiffewpg57nxya5qechm

Preserving privacy in semantic-rich trajectories of human mobility

Anna Monreale, Roberto Trasarti, Chiara Renso, Dino Pedreschi, Vania Bogorny
2010 Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS - SPRINGL '10  
Representing the personal movements as sequences of places visited by a person during her/his movements -semantic trajectory -poses even greater privacy threats w.r.t. raw geometric location data.  ...  The increasing abundance of data about the trajectories of personal movement is opening up new opportunities for analyzing and mining human mobility, but new risks emerge since it opens new ways of intruding  ...  Chiara Renso acknowledges support from CNR Short Term Mobility program and Dino Pedreschi acknowledges support by Google, under the Google Research Award program.  ... 
doi:10.1145/1868470.1868481 dblp:conf/gis/MonrealeTRPB10 fatcat:ruttm6b5u5hwtp56jvc34f3yfe

An Analysis of Location Prediction Models

S. S., E. Akinola
2020 International Journal of Computer Applications  
Classification of mobile users can be regular or random which can be used to ascertain the pattern of the user over a period of time which also helps in planning the movement of the user.  ...  This paper places emphasizes on the relevance of location prediction models in mobile users.  ...  CONCLUSION This research has analyzed various location prediction models, their objectives and also stated their various limitations.  ... 
doi:10.5120/ijca2020920063 fatcat:lstc4uzdrbg3pegwzd2ftnrfsy

On the properties of human mobility

Michela Papandrea, Karim Keramat Jahromi, Matteo Zignani, Sabrina Gaito, Silvia Giordano, Gian Paolo Rossi
2016 Computer Communications  
We show that the number of places visited by each person (Points of Interest -PoIs) is regulated by some properties that are statistically similar among individuals.  ...  The current age of increased people mobility calls for a better understanding of how people move: how many places does an individual commonly visit, what are the semantics of these places, and how do people  ...  The proposed classification and the PoIs and user features provide the basis for understanding human behavior by extracting the semantics of visited places.  ... 
doi:10.1016/j.comcom.2016.03.022 fatcat:n2kiqhey5jghjcebjwr7ui7jbu
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