Results 11 to 20 of about 121,585 (255)
Recommendation System Algorithms on Location-Based Social Networks: Comparative Study
Information, 2022 Currently, social networks allow individuals from all over the world to share ideas, activities, events, and interests over the Internet. Using location-based social networks (LBSNs), users can share their locations and location-related content ...
Abeer Al-Nafjan +2 more
doaj +1 more source
Personality and location-based social networks [PDF]
Computers in Human Behavior, 2015 Location-based social networks (LBSNs) are a recent phenomenon for sharing a presence at everyday locations with others and have the potential to give new insights into human behaviour. To date, due to barriers in data collection, there has been little research into how our personality relates to the categories of place that we visit.
Martin J. Chorley +2 more
openaire +1 more source
Query Processing of Geosocial Data in Location-Based Social Networks
ISPRS International Journal of Geo-Information, 2021 The increasing use of social media and the recent advances in geo-positioning technologies have produced a great amount of geosocial data, consisting of spatial, textual, and social information, to be managed and queried.
Arianna D’Ulizia +2 more
doaj +1 more source
Review of Point of Interest Recommendation Systems in Location-Based Social Networks [PDF]
Jisuanji kexue yu tansuo, 2022 Point of interest recommendation is recently one of the hotspots in the field of location-based social networks and recommendation systems. Understanding the research status of the point of interest recommendation in location-based social networks can ...
CHEN Jiangmei, ZHANG Wende
doaj +1 more source
Mathematics, 2020 Location-based social networks have been widely used. However, due to the lack of effective and safe data management, a large number of privacy disclosures commonly occur.
Xiao Pan, Weizhang Chen, Lei Wu
doaj +1 more source
Location Recommendation Algorithm Based on Location2vec [PDF]
Jisuanji gongcheng, 2019 In the location recommendation application,the traditional collaborative filtering recommendation algorithms are not effective due to the sparseness of the check-in data.In order to improve the recommendation effect and overcome the shortcomings of the ...
DING Yong, WANG Xiang, JIANG Cuiqing
doaj +1 more source
Location prediction in location-based social networks
Global Journal of Information Technology: Emerging Technologies, 2017 Developments in mobile devices and wireless networks have led to the increasing popularity of location-based socialnetworks. These networks allow users to explore new places , share their location, videos and photos and make friends. They give information about the mobility of users, which can be used to improve the networks.
Baydar, Mücahit, ALBAYRAK, Songül
openaire +3 more sources
A Multi-Element Hybrid Location Recommendation Algorithm for Location Based Social Networks
IEEE Access, 2019 In the environment of data explosion, how to make an effective and accurate personalized point of interest (POI) recommendation in location-based social networks (LBSNs) is a challenging and meaningful task.
Ren Yue-Qiang +3 more
doaj +1 more source
LoCaTe: Influence Quantification for Location Promotion in Location-based Social Networks [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 Location-based social networks (LBSNs) such as Foursquare offer a platform for users to share and be aware of each other’s physical movements. As a result of such a sharing of check-in information with each other, users can be influenced to visit (or check-in) at the locations visited by their friends.
Ankita Likhyani +2 more
openaire +3 more sources
Discovering User’s Trends and Routines from Location Based Social Networks
Proceedings, 2018 Location data is a powerful source of information to discover user’s trends and routines. A suitable identification of the user context can be exploited to provide automatically services adapted to the user preferences. In this paper, we define a Dynamic
Sergio Salomón +2 more
doaj +1 more source