IEEE Access, 2020 The location-based social network (LBSN) contains a large amount of user check-in data informations, in order to better improve the recommendation performance and avoid the impact of user check-in data sparsity.
Juan Li, Xiaofeng Wang, Wanjing Feng
doaj +1 more source
The Geography of Social Media Data in Urban Areas: Representativeness and Complementarity
ISPRS International Journal of Geo-Information, 2021 This research sheds light on the relationship between the presence of location-based social network (LBSN) data and other economic and demographic variables in the city of Valencia (Spain). For that purpose, a comparison is made between location patterns
Álvaro Bernabeu-Bautista +3 more
doaj +1 more source
Extracting user spatio-temporal profiles from location based social networks [PDF]
, 2014 Report de RecercaLocation Based Social Networks (LBSN) like Twitter or Instagram are a good source for user spatio-temporal behavior. These social network provide a low rate sampling of user's location information during large intervals of time that can
Béjar Alonso, Javier
core +1 more source
Do people communicate about their whereabouts? Investigating the relation between user-generated text messages and Foursquare check-in places [PDF]
, 2018 The social functionality of places (e.g. school, restaurant) partly determines human behaviors and reflects a region’s functional configuration. Semantic descriptions of places are thus valuable to a range of studies of humans and geographic spaces ...
Li, Ming +2 more
core +1 more source
An Automatic User Grouping Model for a Group Recommender System in Location-Based Social Networks
ISPRS International Journal of Geo-Information, 2018 Spatial group recommendation refers to suggesting places to a given set of users. In a group recommender system, members of a group should have similar preferences in order to increase the level of satisfaction.
Elahe Khazaei, Abbas Alimohammadi
doaj +1 more source
Gender Matters! Analyzing Global Cultural Gender Preferences for Venues Using Social Sensing
, 2017 Gender differences is a phenomenon around the world actively researched by social scientists. Traditionally, the data used to support such studies is manually obtained, often through surveys with volunteers.
Almeida, Jussara M +3 more
core +1 more source
Contextual Attention Recurrent Architecture for Context-aware Venue Recommendation [PDF]
, 2018 Venue recommendation systems aim to effectively rank a list of interesting venues users should visit based on their historical feedback (e.g. checkins).
Kingma Diederik +6 more
core +1 more source
Geographically Insensitive Spatial-Temporal POI Recommendation Based on Heterogeneous Graph Embedding [PDF]
Jisuanji kexue yu tansuoThe increasingly large scale of location-based social networks (LBSN) promotes the rapid development of point-of-interest (POI) recommendation business.
LI Manwen, ZHANG Yueqin, ZHANG Chenwei, ZHANG Zehua
doaj +1 more source
Antioxidants by nature: an ancient feature at the heart of flavonoids' multifunctionality
New Phytologist, Volume 245, Issue 1, Page 11-26, January 2025.
Giovanni Agati +5 more
wiley +1 more source
Electronics, 2019 The surfer and the physical location are two important concepts associated with each other in the social network-based localization service. This work consists of studying urban behavior based on location-based social networks (LBSN) data; we focus ...
Mohamed Sakkari +2 more
semanticscholar +1 more source