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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  
CONCLUSION In this paper, we proposed a geo-social-temporal mining approach to infer location types from location based social networks data.  ...  GEO-SOCIAL PATTERN MINING The section presents a two-step geo-social pattern mining method to compute frequent co-located friendship components.  ...  .: Inferring Location Types with Geo-Social-Temporal Pattern Mining HAIFENG SHEN is an associate professor and the discipline leader of information technology with Peter Faber Business School at Australian  ... 
doi:10.1109/access.2020.3018997 fatcat:rz67ryqm7velblvvspez33kzqq

From where do tweets originate?

Qunying Huang, Guofeng Cao, Caixia Wang
2014 Proceedings of the 7th ACM SIGSPATIAL International Workshop on Location-Based Social Networks - LBSN '14  
Instead of using such hidden geographic cues, this paper develops a GIS approach that can infer the true origin of tweets down to the zip code level by using and mining spatial (geo-tags) and temporal  ...  A number of natural language processing and text-mining algorithms have been developed to extract the geospatial cues (e.g., place names) to infer locations of content creators from publicly available  ...  Two steps are developed over these datasets to infer zone types: determining the type of locations where online social activities occur using urban land use data and mining geo-location based on the Google  ... 
doi:10.1145/2755492.2755494 dblp:conf/gis/HuangCW14 fatcat:psu4nnwu4vehha5hzt66vpy2wm

Mining and correlating traffic events from human sensor observations with official transport data using self-organizing-maps

Enrico Steiger, Bernd Resch, João Porto de Albuquerque, Alexander Zipf
2016 Transportation Research Part C: Emerging Technologies  
With the Geo-SOM, consistent cluster characteristics of disruptions show similar temporal patterns at certain geographic locations and help to uncover complex topological structures of the London street  ...  As a further option, users can geotag their tweets with a geo-location acquired by their mobile devices.  ...  Mining and correlating traffic events from human sensor observations with official transport data using self-organizing-maps.  ... 
doi:10.1016/j.trc.2016.10.010 fatcat:yhtj66tqozhxdil3hq62n34tlq

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  
INDEX TERMS Data mining, data analysis, pattern recognition, detection algorithms, inference mechanisms, inference algorithms.  ...  The geographic co-movement pattern has rarely been used by the police force to infer social connections, although it has been prevalent in other fields.  ...  In our study, we focus on spatio-temporal trajectories for social link inference. Group pattern mining over trajectories is an effective way to study the spatio-temporal connections between objects.  ... 
doi:10.1109/access.2020.2968131 fatcat:ffrhv7vdk5gihp3jgek3md66fu

Mapping Dynamic Urban Land Use Patterns with Crowdsourced Geo-Tagged Social Media (Sina-Weibo) and Commercial Points of Interest Collections in Beijing, China

Yandong Wang, Teng Wang, Ming-Hsiang Tsou, Hao Li, Wei Jiang, Fengqin Guo
2016 Sustainability  
We collected 9.5 million geo-tagged Chinese social media (Sina-Weibo) messages from January 2014 to July 2014 in the urban core areas of Beijing and compared them with 385,792 commercial Points of Interest  ...  Human activity patterns, topics of discussion on social media, and the distribution of urban facilities in different regions were combined and analyzed to infer urban land use patterns.  ...  Analysis of Different Clusters with Associated Land Use Types By analyzing social media message (Sina-Weibo) temporal trend patterns in different areas, we can estimate different types of urban land use  ... 
doi:10.3390/su8111202 fatcat:3ldfnfqdqnbrljkuniz72oi3ta

Discover Patterns and Mobility of Twitter Users—A Study of Four US College Cities

Yue Li, Qinghua Li, Jie Shan
2017 ISPRS International Journal of Geo-Information  
Mining user behaviours: A study of check-in patterns in location based social networks.  ...  We expect to explore the spatial and temporal patterns of geo-tagged tweets by various geospatial mining methods.  ... 
doi:10.3390/ijgi6020042 fatcat:ttjdzloukjd7znsdfp2bm4uoli

Guest editorial: big spatial data

Raju Vatsavai, Varun Chandola
2016 Geoinformatica  
Big data is currently the hottest topic for data researchers and scientists with huge interests from the industry and federal agencies alike, as evident in the recent White House initiative on BBig data  ...  However, recent advances in instrumentation and computation, and advent of social media is making the spatiotemporal data even bigger, putting several constraints on data analytics capabilities.  ...  Spatiotemporal co-occurring patterns represent subsets of event types that occur together in both space and time.  ... 
doi:10.1007/s10707-016-0269-7 fatcat:jt53iqmzrngkfcq4n4ixikchhu

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

Geotagging in multimedia and computer vision—a survey

Jiebo Luo, Dhiraj Joshi, Jie Yu, Andrew Gallagher
2010 Multimedia tools and applications  
Geo-tagging is a fast-emerging trend in digital photography and community photo sharing.  ...  The presence of geographically relevant metadata with images and videos has opened up interesting research avenues within the multimedia and computer vision domains.  ...  After analyzing the location and time metadata available in geo-tagged images on Flickr, the authors were able to detect the temporal and spatial patterns and categorizing the relevant tags with reasonable  ... 
doi:10.1007/s11042-010-0623-y fatcat:esd7subpbjhntpes6quvngtwti

What is this place? Inferring place categories through user patterns identification in geo-tagged tweets

Deborah Falcone, Cecilia Mascolo, Carmela Comito, Domenico Talia, Jon Crowcroft
2014 Proceedings of the 6th International Conference on Mobile Computing, Applications and Services  
A supervised learning framework takes the tweets spatial-temporal features and determines human dynamics which we use to infer the place category.  ...  While some location based online social network services (e.g., Foursquare) allow users to tag the places they visit, this is not an automated process but one which requires the user help.  ...  ACKNOWLEDGMENT The work presented in this paper has been partially supported by European Commission, European Social Fund (ESF), Regione Calabria, and COST program Action IC1305, 'Network for Sustainable  ... 
doi:10.4108/icst.mobicase.2014.257683 dblp:conf/mobicase/FalconeMCTC14 fatcat:mxreore47rgkzilqfzbb24zp6i

Modeling Implicit Communities using Spatio-Temporal Point Processes from Geo-tagged Event Traces [article]

Ankita Likhyani and Vinayak Gupta and Srijith P. K. and Deepak P. and Srikanta Bedathur
2020 arXiv   pre-print
COLAB captures the semantic features of the location, user-to-user influence along with spatial and temporal preferences of users.  ...  The location check-ins of users through various location-based services such as Foursquare, Twitter, and Facebook Places, etc., generate large traces of geo-tagged events.  ...  [14] is the closest work to our work, where authors determine the patterns from geo located posts from twitter.  ... 
arXiv:2006.07580v1 fatcat:ep4zgc2iw5bjvetkl2gbfpkabi

A Survey on Trajectory Data Mining: Techniques and Applications

Zhenni Feng, Yanmin Zhu
2016 IEEE Access  
In this paper, we survey various applications of trajectory data mining, e.g., path discovery, location prediction, movement behavior analysis, and so on.  ...  A trajectory is typically represented by a sequence of timestamped geographical locations. A wide spectrum of applications can benefit from the trajectory data mining.  ...  Then, human behavior is inferred from these patterns which are mined from trajectory data.  ... 
doi:10.1109/access.2016.2553681 fatcat:bwz3c6oyfjahroihps7i3wo76q

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.  ...  The temporal feature captures both the time of the location visit and the temporal patterns associated with significant locations. Using these features, Noulas et al.  ... 
doi:10.26599/bdma.2018.9020010 dblp:journals/bigdatama/WuLSTP18 fatcat:3ogap5xsxffjxazjm7chcnqu3u

Social sensing of urban land use based on analysis of Twitter users' mobility patterns

Aiman Soliman, Kiumars Soltani, Junjun Yin, Anand Padmanabhan, Shaowen Wang, Jaymie Meliker
2017 PLoS ONE  
Scatter plots of temporal signatures of individual key locations.  ...  OPEN ACCESS Citation: Soliman A, Soltani K, Yin J, Padmanabhan A, Wang S (2017) Social sensing of urban land use based on analysis of Twitter users' mobility patterns. PLoS ONE 12(7): e0181657.  ...  Furthermore, the temporal patterns of tweeting at these locations are similar for the majority of users and correlated with the locations land use types.  ... 
doi:10.1371/journal.pone.0181657 pmid:28723936 pmcid:PMC5517059 fatcat:2tcmzyedzzdptcnqzh6oyxx54i

Recommendations in location-based social networks: a survey

Jie Bao, Yu Zheng, David Wilkie, Mohamed Mokbel
2015 Geoinformatica  
Recent advances in localization techniques have fundamentally enhanced social networking services, allowing users to share their locations and location-related contents, such as geo-tagged photos and notes  ...  This article presents a panorama of the recommender systems in location-based social networks with a balanced depth, facilitating research into this important research theme.  ...  , 133] . 1) Mining Geo-tagged social media.  ... 
doi:10.1007/s10707-014-0220-8 fatcat:3ivmtrnvkfhshl72gd33h4aola
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