Results 51 to 60 of about 228 (183)
Revisiting User Mobility and Social Relationships in LBSNs: A Hypergraph Embedding Approach [PDF]
The World Wide Web Conference, 2019 Location Based Social Networks (LBSNs) have been widely used as a primary data source to study the impact of mobility and social relationships on each other. Traditional approaches manually define features to characterize users' mobility homophily and social proximity, and show that mobility and social features can help friendship and location ...
Yang, Dingqi +3 more
openaire +1 more source
A Paradigm of Temporal‐Weather‐Aware Transition Pattern for POI Recommendation
CAAI Transactions on Intelligence Technology, Volume 10, Issue 6, Page 1675-1687, December 2025.ABSTRACT Point of interest (POI) recommendation analyses user preferences through historical check‐in data. However, existing POI recommendation methods often overlook the influence of weather information and face the challenge of sparse historical data for individual users.
Junyang Chen +6 more
wiley +1 more source
Personalized Recommendation of Tourist Attractions based on LBSN
DEStech Transactions on Computer Science and Engineering, 2018 Photos metadata in Location-Based Social Networks (LBSN) contain rich time and space information, these metadata provide the basis for the research of personalized recommendation of tourist attractions. The existing methods have many problems such as low accuracy of recommendation and single type of attractions recommendation.
Huifang Lv +4 more
openaire +2 more sources
Context-Aware Group-Oriented Location Recommendation in Location-Based Social Networks
ISPRS International Journal of Geo-Information, 2019 Location-based social networking services have attracted great interest with the growth of smart mobile devices. Recommending locations for users based on their preferences is an important task for location-based social networks (LBSNs).
Elahe Khazaei, Abbas Alimohammadi
doaj +1 more source
Location Regularization-Based POI Recommendation in Location-Based Social Networks
Information, 2018 POI (point-of-interest) recommendation as one of the efficient information filtering techniques has been widely utilized in helping people find places they are likely to visit, and many related methods have been proposed.
Lei Guo, Haoran Jiang, Xinhua Wang
doaj +1 more source
PredicTour: Predicting Mobility Patterns of Tourists Based on Social Media User’s Profiles
IEEE Access, 2022 This paper proposes PredicTour, an approach to process check-ins made by users of location-based social networks (LBSNs), and predict mobility patterns of tourists visiting new countries with or without previous visiting records.
Helen C. Mattos Senefonte +3 more
doaj +1 more source
ISPRS International Journal of Geo-Information, 2015 The relevance of geographic information to mobile users must be evaluated by taking into account the usage context. This paper assumes that emerging Location-based Social Networks (LBSNs) contain contextual information rich enough to be used in order to ...
Ming Li, Yeran Sun, Hongchao Fan
doaj +1 more source
Friendship prediction model based on factor graphs integrating geographical location
CAAI 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
Discovering Travel Community for POI Recommendation on Location-Based Social Networks
Complexity, 2019 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).
Lei Tang +5 more
doaj +1 more source
A Mobility Model for Synthetic Travel Demand From Sparse Traces
IEEE Open Journal of Intelligent Transportation Systems, 2022 Knowing how much people travel is essential for transport planning. Empirical mobility traces collected from call detail records (CDRs), location-based social networks (LBSNs), and social media data have been used widely to study mobility patterns ...
Yuan Liao +4 more
doaj +1 more source