Results 71 to 80 of about 228 (183)

Point-of-Interest Preference Model Using an Attention Mechanism in a Convolutional Neural Network. [PDF]

open access: yesBioengineering (Basel), 2023
Kasgari AB   +5 more
europepmc   +1 more source

Locative Media and Sociability: Using Location-Based Social Networks to Coordinate Everyday Life

open access: yesArchitecture_MPS, 2018
Foursquare was a mobile social networking application that enabled people to share location with friends in the form of “check-ins.” The visualization of surrounding known social connections as well as unknown others has the potential to impact how ...
doaj   +2 more sources

The Application of Lite-GRU Embedding and VAE-Augmented Heterogeneous Graph Attention Network in Friend Link Prediction for LBSNs

open access: yesApplied Sciences
Friend link prediction is an important issue in recommendation systems and social network analysis. In Location-Based Social Networks (LBSNs), predicting potential friend relationships faces significant challenges due to the diversity of user behaviors ...
Ziteng Yang   +3 more
doaj   +1 more source

Examining the effects of proximity to rail transit on travel to non-work destinations: Evidence from Yelp data for cities in North America and Europe

open access: yesJournal of Transport and Land Use, 2019
Urban planners often seek to establish land use patterns around transit stations that encourage non-auto travel. However, the willingness of travelers to use different modes in the vicinity of transit remains understudied, in part because of the lack of ...
Zhiqiu Jiang, Andrew Mondschein
doaj   +1 more source

Contrasting social and non-social sources of predictability in human mobility. [PDF]

open access: yesNat Commun, 2022
Chen Z   +6 more
europepmc   +1 more source

Context-Aware Knowledge Graph Learning for Point-of-Interest Recommendation

open access: yesISPRS International Journal of Geo-Information
Existing point-of-interest (POI) recommendation methods often fail to capture complex contextual dependencies and suffer from severe data sparsity in location-based social networks (LBSNs).
Yan Zhou   +3 more
doaj   +1 more source

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