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Discovery of spatio-temporal patterns from location-based social networks

J. Béjar, S. Álvarez, D. García, I. Gómez, L. Oliva, A. Tejeda, J. Vázquez-Salceda
2015 Journal of experimental and theoretical artificial intelligence (Print)  
Location Based Social Networks (LBSN) like Twitter or Instagram are a good source for user spatio-temporal behavior.  ...  The aim of this paper is twofold, first to analyze the frequent spatio-temporal patterns that users share when living and visiting a city.  ...  Introduction Location Based Social Networks (Zheng, 2011) , like for example Twitter or Instagram, are an important source of information for studying the geospatial and temporal behavior of a large number  ... 
doi:10.1080/0952813x.2015.1024492 fatcat:ny4kybuwjrh4rdasskb3cig664

Inferring user relationship from hidden information in WLANs

Ningning Cheng, Prasant Mohapatra, Mathieu Cunche, Mohamed Ali Kaafar, Roksana Boreli, Srikanth Krishnamurthy
2012 MILCOM 2012 - 2012 IEEE Military Communications Conference  
proximity and spatio-temporal behavior.  ...  With ever increasing usage of handheld devices and vast deployment of wireless networks, we observe that it is possible to collect data from mobile devices and reveal personal relationships of their owners  ...  The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory  ... 
doi:10.1109/milcom.2012.6415713 dblp:conf/milcom/ChengMCKBK12 fatcat:6movqm25ardltl4ufkh5mfycae

A Survey on Destination Prediction Using Trajectory Data Mining Technique

Banupriya C S
2016 International Journal Of Engineering And Computer Science  
Mobility pattern of the user is predicted using next check-in data. Prediction features that exploit different information dimensions about users based on venue prediction.  ...  Trajectory is represented by a sequence of time stamped geographical location. Trajectories provide intelligence to estimate, compare and construct candidate routes by historical road network.  ...  Based on the set of prediction features information is exploited between types of places, mobility flows between venue and spatio-temporal characteristics of check-in pattern.  ... 
doi:10.18535/ijecs/v5i12.67 fatcat:lzg2mq6fdnfstj3ll4s76a35je

Understanding the Spatio-temporal Topic Dynamics of Covid-19 using Nonnegative Tensor Factorization: A Case Study [article]

Thirunavukarasu Balasubramaniam, Richi Nayak, Md Abul Bashar
2020 arXiv   pre-print
This paper proposes a tensor-based representation of social media data and Non-negative Tensor Factorization (NTF) to identify the topics discussed in social media data along with the spatio-temporal topic  ...  Given the high complexity and poor quality of the huge social media data, an effective spatio-temporal topic detection method is needed.  ...  or any of its cities (a) term × location matrix used to generate topics based on spatio-temporal patterns from social media data.  ... 
arXiv:2009.09253v1 fatcat:xhm5p3q7y5aj5blwhiuof2qb6m

Revealing spatio-temporal interaction patterns behind complex cities [article]

Chenxin Liu, Yu Yang, Bingsheng Chen, Tianyu Cui, Fan Shang, Jingfang Fan, Ruiqi Li
2022 arXiv   pre-print
Massive cellphone data enable us to construct interaction networks based on spatio-temporal co-occurrence of individuals.  ...  patterns of spatio-temporal interactions in cities.  ...  Madina Doumbia from University Péléforo Gon Coulibaly for providing the shapefile of Abidjan at the commune resolution.  ... 
arXiv:2201.02117v2 fatcat:dvs2pycxunccvlek44xzw6gz6u

Understanding the Spatio-temporal Topic Dynamics of Covid-19 using Nonnegative Tensor Factorization: A Case Study

Thirunavukarasu Balasubramaniam, Richi Nayak, Md Abul Bashar
2020 2020 IEEE Symposium Series on Computational Intelligence (SSCI)  
or any of its cities (a) term × location matrix used to generate topics based on spatio-temporal patterns from social media data.  ...  NTF BASED SPATIO-TEMPORAL TOPIC DISCOVERY The proposed NTF based spatio-temporal topic dynamics discovery method consists of the following three components: 1) Data representation, 2) Non-negative Tensor  ... 
doi:10.1109/ssci47803.2020.9308265 fatcat:lgwa2hn4jja23iv3c7th7goinm

Learning Automaton Based On-Line Discovery and Tracking of Spatio-temporal Event Patterns [chapter]

Anis Yazidi, Ole-Christoffer Granmo, Min Lin, Xifeng Wen, B. John Oommen, Martin Gerdes, Frank Reichert
2010 Lecture Notes in Computer Science  
social networking applications.  ...  Our scheme is based on maintaining a collection of hypotheses, each one conjecturing a specific spatio-temporal event pattern.  ...  Learning Automaton Based On-Line Discovery and Tracking of Spatio-temporal Event Patterns We base our work on the principles of LA [9, 11] .  ... 
doi:10.1007/978-3-642-15246-7_31 fatcat:sw7kvcukivdjtdmpbdc5elmc3m

A spatio-temporal-textual crime search engine

Xutong Liu, Changshu Jian, Chang-Tien Lu
2010 Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS '10  
It's getting more difficult considering the subjectivity and vagueness of information retrieval from narratives of victims or witness and online documents of social networks.  ...  It's a big challenge to reveal inherent ST(spatio-temporal) correlations among mass crime information.  ...  INTRODUCTION Crime activity reports available from victims, governmental organizations, news press, and social networks play a significant role in public safety, including crime prevention, suppression  ... 
doi:10.1145/1869790.1869881 dblp:conf/gis/LiuJL10 fatcat:o2fjulzz6vdulpz3jriaaklne4

Inferring Location Types with Geo-Social-Temporal Pattern Mining

Tarique Anwar, Kewen Liao, S Angelic, Timos Sellis, A. S. M. Kayes, Haifeng Shen
2020 IEEE Access  
INDEX TERMS Location based social networks, Spatial data mining, Co-located friendships, Geo-socialtemporal patterns I. INTRODUCTION  ...  In this paper, we propose a pattern mining approach, using the geo-social-temporal data collected from LBSNs, to infer types of different locations.  ...  CONCLUSION In this paper, we proposed a geo-social-temporal mining approach to infer location types from location based social networks data.  ... 
doi:10.1109/access.2020.3018997 fatcat:rz67ryqm7velblvvspez33kzqq

Spatio-Temporal Data Mining: A Survey of Problems and Methods [article]

Gowtham Atluri, Anuj Karpatne, Vipin Kumar
2017 arXiv   pre-print
Based on the nature of the data mining problem studied, we classify literature on spatio-temporal data mining into six major categories: clustering, predictive learning, change detection, frequent pattern  ...  Large volumes of spatio-temporal data are increasingly collected and studied in diverse domains including, climate science, social sciences, neuroscience, epidemiology, transportation, mobile health, and  ...  Hence, during the evaluation of patterns in network-based representations of ST rasters, it is important to filter out patterns arising from spatially neighboring locations for the discovery of long-range  ... 
arXiv:1711.04710v2 fatcat:di3fxigwobeb3db5kcdvlhbe7i

Heuristic Search Based Feature Selection and Discretive Self-Organized Map Clustering for Spatio-Temporal Pattern Discovery

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Initially, the Heuristic Best-First Search Algorithm is used for selecting the relevant Spatio-temporal features from the large dataset for pattern discovery.  ...  Spatio-temporal pattern discovery is an essential one in data mining for predictive analytics.  ...  Detection of Spatio-temporal patterns was presented in [16] from the location-based social networks. But it failed to detect the temporal dimension of the data-set.  ... 
doi:10.35940/ijitee.j1035.08810s19 fatcat:cxrs27swxnbnhimo65ye6436o4

Social Network Discovery by Mining Spatio-Temporal Events

Hady W. Lauw, Ee-Peng Lim, HweeHwa Pang, Teck-Tim Tan
2005 Computational and mathematical organization theory  
We call these spatio-temporal co-occurrences events, which we use to establish relationships between pairs of individuals.  ...  Knowing patterns of relationship in a social network is very useful for law enforcement agencies to investigate collaborations among criminals, for businesses to exploit relationships to sell products,  ...  Finally, we would also look at how patterns of mobility in spatio-temporal data, concerning speeds and sequence of locations traversed, may be used in mining social networks.  ... 
doi:10.1007/s10588-005-3939-9 fatcat:bhuevyw7vze6pclpmapinl2mfa

Resonance - An Intelligence Analysis Framework for Social Connection Inference via Mining Co-Occurrence Patterns over Multiplex Trajectories

Shengjie Min, Guangchun Luo, Zhan Gao, Jing Peng, Ke Qin
2020 IEEE Access  
Diverse kinds of trajectories from the sensor networks provide an unprecedented opportunity for intelligence analysis.  ...  Firstly, We constructed the foundation for the discovery of co-occurrence events, namely space-time resonance honeycomb. It consists of multiple polygonal zones over sensor networks.  ...  ACKNOWLEDGMENT The authors would like to thank the experts from Sichuan Provincial Public Security Department and the Public Security Bureau of Ganzi Autonomous Prefecture who provided insight and expertise  ... 
doi:10.1109/access.2020.2968131 fatcat:ffrhv7vdk5gihp3jgek3md66fu

Spatio-Temporal Analytics for Exploring Human Mobility Patterns and Urban Dynamics in the Mobile Age

Song Gao
2014 Spatial Cognition and Computation  
In this research, we present a spatio-temporal analytical framework including spatiotemporal visualization (STV), space-time kernel density estimation (STKDE), and spatio-temporal-autocorrelation-analysis  ...  The spatial order of weighted matrix was found to have more significant effects than the temporal neighbors on influencing the autocorrelation strength of hourly phone calls.  ...  It could help the identification of individual-based spatio-temporal recurring trends and group-based similarity patterns.  ... 
doi:10.1080/13875868.2014.984300 fatcat:g3nxghutend3lgik5hrwyqti6u

User modeling for point-of-interest recommendations in location-based social networks: the state-of-the-art [article]

Shudong Liu
2017 arXiv   pre-print
, geographical information-based user modeling, spatio-temporal information-based user modeling, and geo-social information-based user modeling.  ...  Location-based social networks(LBSNs)allow users to check-in at a physical location and share daily tips on points-of-interest (POIs) with their friends anytime and anywhere.  ...  Acknowledgements This work is supported by National Scien ce Foundation of China (NO. 61602518) and Open Foundation of Hubei Key Laboratory of Intelligent Geo-Information Processing (No.K  ... 
arXiv:1712.06768v1 fatcat:nzmsjj6kjzby7ldi3czf6zlkye
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