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Recommendations in location-based social networks: a survey

Jie Bao, Yu Zheng, David Wilkie, Mohamed Mokbel
2015 Geoinformatica  
We refer to these social networks as location-based social networks (LBSNs).  ...  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  ...  Community discovery.  ... 
doi:10.1007/s10707-014-0220-8 fatcat:3ivmtrnvkfhshl72gd33h4aola

Social relationships and temp-spatial behaviors based Community Discovery to improve cyber security practices

Jiuxin Cao, Weijia Liu, Biwei Cao, Pan Wang, Shancang Li, Bo Liu, Muddesar Iqbal
2019 IEEE Access  
This paper proposes a LBSN homogeneous network model (LSHNM) based on the user social relations and temp-spatial behaviors to calculate the user similarity relations in multidimensional features and construct  ...  Cyber security significantly relies on the dynamic communities in social networks. The location-based social network (LBSN) is a new type of social system that has sprung up recently that.  ...  CONCLUSION This paper focus on community discovery problem in LBSN from user social relations, temp-spatial distribution and behavioral patterns characteristics.  ... 
doi:10.1109/access.2019.2931937 fatcat:jcic2apttngovhipbvs4cirk24

Location Based Social Networks - Definition, Current State of the Art and Research Agenda

Oliver Roick, Susanne Heuser
2013 Transactions on GIS  
Sites with location based features or the creation of new ones exclusively around geographic information.  ...  This paper presents a comprehensive definition of this special type of Social Network Sites and an overview of research activities, which are currently conducted using the data.  ...  Second, the prediction of social ties between members of an online social network community based on relative geographic distance on the one hand and further based the on number of co-location occurrences  ... 
doi:10.1111/tgis.12032 fatcat:plrjoafm7vcutfeieoss7jruqq

Discovering Travel Community for POI Recommendation on Location-Based Social Networks

Lei Tang, Dandan Cai, Zongtao Duan, Junchi Ma, Meng Han, Hanbo Wang
2019 Complexity  
Point-of-interest (POI) recommendations are a popular form of personalized service in which users share their POI location and related content with their contacts in location-based social networks (LBSNs  ...  The probability of POIs based on users' historical trip data and interests in the same topics can be calculated.  ...  (i) We generalize POI recommendations by detecting communities from social interactions and semantics in the spatial movements.  ... 
doi:10.1155/2019/8503962 fatcat:a5y6gp2mmjbezeoqmu3ojz2mla

SoLoMo cities: socio-spatial city formation detection and evolution tracking approach

Sara Elhishi, Mervat Abu Elkheir, Ahmed Abou Elfetouh
2021 International Journal of Business Intelligence and Data Mining  
We analyse the role of LBSN check-ins using social community detection methods to extract city structured communities, which we call 'SoLoMo cities', using a modified version of Louvain algorithm, then  ...  The findings of the experiments on the Brightkite dataset can be summarised as follows: online users' check-in activities reveal a set of well-formed physical land spaces of city's communities, the concentration  ...  The analysis involved common social followers of the event and related topics on Wikipedia.  ... 
doi:10.1504/ijbidm.2021.111743 fatcat:h6c7tawt4zefti25ql6v2zwvka

Data Analysis on Location-Based Social Networks [chapter]

Huiji Gao, Huan Liu
2013 Mobile Social Networking  
The availability of large amounts of geographical and social data on LBSNs provides an unprecedented opportunity to study human mobile behavior through data analysis in a spatial-temporal-social context  ...  The rapid growth of location-based social networks (LBSNs) has greatly enriched people's urban experience through social media and attracted increasing number of users in recent years.  ...  [8] extended the research on LBSNs to social community, and discovered that the rise of social groups is affected by both social and spatial factors.  ... 
doi:10.1007/978-1-4614-8579-7_8 fatcat:m2yot724ufe63o5jughtjun33m

A Graph-Based Taxonomy of Recommendation Algorithms and Systems in LBSNs

Pavlos Kefalas, Panagiotis Symeonidis, Yannis Manolopoulos
2016 IEEE Transactions on Knowledge and Data Engineering  
Recently, location-based social networks (LBSNs) gave the opportunity to users to share geo-tagged information along with photos, videos, and SMSs.  ...  In this paper, we present and compare 16 real life LBSNs, bringing into surface their advantages/ disadvantages, their special functionalities, and their impact in the mobile social Web.  ...  Their algorithm is named Social Communities in Location based Networks (SCLN). Their study exploits social and spatial properties of these networks.  ... 
doi:10.1109/tkde.2015.2496344 fatcat:6gikvhjovvaj5dqvsu7tqvayu4

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  
The advent of location-based online social networks (LBSNs) has made it much easier to collect voluminous data about users in different locations or spatial regions.  ...  In this paper, we propose a pattern mining approach, using the geo-social-temporal data collected from LBSNs, to infer types of different locations.  ...  The second challenge is to characterise the spatial, social, and temporal patterns individually as well as combined altogether.  ... 
doi:10.1109/access.2020.3018997 fatcat:rz67ryqm7velblvvspez33kzqq

Joint Modeling of Users' Interests and Mobility Patterns for Point-of-Interest Recommendation

Hongzhi Yin, Bin Cui, Zi Huang, Weiqing Wang, Xian Wu, Xiaofang Zhou
2015 Proceedings of the 23rd ACM international conference on Multimedia - MM '15  
To cope with this challenge, we propose a unified probabilistic generative model, Topic-Region Model (TRM), to simultaneously discover the semantic, temporal and spatial patterns of users' check-in activities  ...  , and to model their joint effect on users' decision-making for POIs.  ...  The work described in this paper is partially supported by ARC Discovery Project (DP140103171), the National Natural Science  ... 
doi:10.1145/2733373.2806339 dblp:conf/mm/YinCHWWZ15 fatcat:qeznfw7owzhypdrkuyqcthplyq

Trajectory-based Visual Analytics for Anomalous Human Movement Analysis using Social Media [article]

Junghoon Chae, Yuchen Cui, Yun Jang, Guizhen Wang, Abish Malik, David S. Ebert
2015 EuroVis Workshop on Visual Analytics (EuroVA)  
We extract trajectories from location-based social networks and cluster the trajectories into sets of similar sub-trajectories in order to discover common human movement patterns.  ...  The rapid development and increasing availability of mobile communication and location acquisition technologies allow people to add location data to existing social networks so that people share location-embedded  ...  However, the rapid development and increasing availability of mobile communication and location acquisition devices allow people to share location data using location-based social networks (LBSNs).  ... 
doi:10.2312/eurova.20151102 dblp:conf/vissym/ChaeCJWME15 fatcat:enzzykcu5nfvrkmz6el3fjqicm

Geo-SAGE

Weiqing Wang, Hongzhi Yin, Ling Chen, Yizhou Sun, Shazia Sadiq, Xiaofang Zhou
2015 Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15  
With the rapid development of location-based social networks (LB-SNs), spatial item recommendation has become an important means to help people discover attractive and interesting venues and events, especially  ...  Geo-SAGE considers both user personal interests and the preference of the crowd in the target region, by exploiting both the co-occurrence pattern of spatial items and the content of spatial items.  ...  POI recommendation with temporal effect mainly leverages temporal cyclic patterns and temporal sequential patterns on LBSNs. Gao et al.  ... 
doi:10.1145/2783258.2783335 dblp:conf/kdd/WangYCSSZ15 fatcat:3xvgqupctrfl5h46ilwuxg6fka

Identifying opportunity places for urban regeneration through LBSNs

Pablo Martí, Clara García-Mayor, Leticia Serrano-Estrada
2019 Cities  
The use of location based social networks-LBSNs-for diagnosing phenomena in contemporary cities is evolving at a fast pace.  ...  T The paper's novel approach lies in the study of inner-city neighborhood spatial and functional dynamics and patterns from a two-fold perspective: i.  ...  Overlapping several LBSNs consolidates the information provided by single sources in relation to spatial patterns, facilitating richer analysis and interpretation of the results in a case study.  ... 
doi:10.1016/j.cities.2019.02.001 fatcat:epxpzc4nwzgyngnaker6e4s2ey

Discovering interpretable geo-social communities for user behavior prediction

Hongzhi Yin, Zhiting Hu, Xiaofang Zhou, Hao Wang, Kai Zheng, Quoc Viet Hung Nguyen, Shazia Sadiq
2016 2016 IEEE 32nd International Conference on Data Engineering (ICDE)  
To improve the accuracy and interpretability of community discovery, we propose to infer users' social communities by incorporating their spatiotemporal data and semantic information.  ...  Social community detection is a growing field of interest in the area of social network applications, and many approaches have been developed, including graph partitioning, latent space model, block model  ...  location-based social networks (LBSNs) and event-based social networks (EBSNs) [16] , [22] .  ... 
doi:10.1109/icde.2016.7498303 dblp:conf/icde/YinHZWZHS16 fatcat:7hosxlczufcu5k2u5n2hpkungy

Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation [article]

Weiqing Wang, Hongzhi Yin, Ling Chen, Yizhou Sun, Shazia Sadiq, Xiaofang Zhou
2015 arXiv   pre-print
With the rapid development of location-based social networks (LBSNs), spatial item recommendation has become an important means to help people discover attractive and interesting venues and events, especially  ...  Geo-SAGE considers both user personal interests and the preference of the crowd in the target region, by exploiting both the co-occurrence pattern of spatial items and the content of spatial items.  ...  POI recommendation with temporal effect mainly leverages temporal cyclic patterns and temporal sequential patterns on LBSNs. Gao et al.  ... 
arXiv:1503.03650v1 fatcat:i2c25jsuyzc2ncfbi6cnocjztu

Location-Based Social Networks: Users [chapter]

Yu Zheng
2011 Computing with Spatial Trajectories  
In this chapter, we introduce and define the meaning of location-based social network (LBSN) and discuss the research philosophy behind LBSNs from the perspective of users and locations.  ...  The inferred similarity represents the strength of connection between two users in a locationbased social network, and can enable friend recommendations and community discovery.  ...  Evaluating the applications in a location-based social network, such as friend recommendation and community discovery, is a non-trivial research topic due to the following challenges: data, ground truth  ... 
doi:10.1007/978-1-4614-1629-6_8 fatcat:wblv2rposjfijdioqjnnlfluoe
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