Results 31 to 40 of about 699,381 (334)

Joint Promotion Partner Recommendation Systems Using Data from Location-Based Social Networks

open access: yesISPRS International Journal of Geo-Information, 2021
Joint promotion is a valuable business strategy that enables companies to attract more customers at lower operational cost. However, finding a suitable partner can be extremely difficult.
Yi-Chung Chen   +3 more
doaj   +1 more source

Context-Specific Point-of-Interest Recommendation Based on Popularity-Weighted Random Sampling and Factorization Machine

open access: yesISPRS International Journal of Geo-Information, 2021
Point-Of-Interest (POI) recommendation not only assists users to find their preferred places, but also helps businesses to attract potential customers. Recent studies have proposed many approaches to the POI recommendation.
Dongjin Yu   +3 more
doaj   +1 more source

The impact of location privacy on opportunistic networks

open access: yes, 2011
Opportunistic networking involves forwarding messages between proximate users, who may or may not know one another. This assumes that users are willing to forward messages to each other. This assumption may not hold if users are concerned about using the
Parris, Iain   +3 more
core   +1 more source

Social Relationships and Temp-Spatial Behaviors Based Community Discovery to Improve Cyber Security Practices

open access: yesIEEE Access, 2019
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.
Jiuxin Cao   +6 more
doaj   +1 more source

Reliable online social network data collection

open access: yes, 2012
Large quantities of information are shared through online social networks, making them attractive sources of data for social network research. When studying the usage of online social networks, these data may not describe properly users’ behaviours.
Parris, Iain   +5 more
core   +1 more source

Spatio-temporal aware privacy-preserving scheme in LBS

open access: yesTongxin xuebao, 2018
Location-based service (LBS) brings a lot of conveniences in people’s daily life,but the conveniences are accompanied with the leaking of privacy.A dummy-based location-preserving scheme was proposed,which took the correlation between spatial issues and ...
Weihao LI   +3 more
doaj   +2 more sources

Friendship prediction model based on factor graphs integrating geographical location

open access: yesCAAI Transactions on Intelligence Technology, 2020
With the development of network services and location-based systems, many mobile applications begin to use users’ geographical location to provide better services. In terms of social networks, geographical location is actively shared by users.
Liang Chen   +7 more
doaj   +1 more source

Context-Aware Point-of-Interest Recommendation Based on Similar User Clustering and Tensor Factorization

open access: yesISPRS International Journal of Geo-Information, 2023
The rapid development of big data technology and mobile intelligent devices has led to the development of location-based social networks (LBSNs). To understand users’ behavioral patterns and improve the accuracy of location-based services, point-of ...
Yan Zhou, Kaixuan Zhou, Shuaixian Chen
doaj   +1 more source

On Neighborhood Effects in Location-Based Social Networks

open access: yes2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015
In this paper, we analyze factors that determine the check-in decisions of users on venues using a location-based social network dataset. Based on a Foursquare dataset constructed from Singapore-based users, we devise a stringent criteria to identify the actual home locations of a subset of users.
Thanh-Nam Doan   +2 more
openaire   +3 more sources

Toward local family relationship discovery in location-based social network

open access: yes, 2017
The local family relationship discovery problem in location-based social network (LBSN) services is to identify whether two local residents in a city belong to the same family or not by using their check-in traces on LBSNs.
Brian Mann   +7 more
core   +1 more source

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