Model-agnostic decentralized collaborative learning for on-device POI recommendation
As an indispensable personalized service in Location-based Social Networks (LBSNs), the
next Point-of-Interest (POI) recommendation aims to help people discover attractive and …
next Point-of-Interest (POI) recommendation aims to help people discover attractive and …
Repetition and Exploration in Sequential Recommendation
In several recommendation scenarios, including next basket recommendation, the
importance of repetition and exploration has been discovered and studied. Sequential …
importance of repetition and exploration has been discovered and studied. Sequential …
Point-of-interest recommendation model considering strength of user relationship for location-based social networks
Y Zhou, G Yang, B Yan, Y Cai, Z Zhu - Expert Systems with Applications, 2022 - Elsevier
Point of interest (POI) recommendation systems have drawn the attention of researchers in
multiple domains, particularly location-based social networks (LBSNs). However, owing to …
multiple domains, particularly location-based social networks (LBSNs). However, owing to …
Decentralized Collaborative Learning with Adaptive Reference Data for On-Device POI Recommendation
In Location-based Social Networks (LBSNs), Point-of-Interest (POI) recommendation helps
users discover interesting places. There is a trend to move from the conventional cloud …
users discover interesting places. There is a trend to move from the conventional cloud …
Healthwalks: Sensing fine-grained individual health condition via mobility data
Can health conditions be inferred from an individual's mobility pattern? Existing research
has discussed the relationship between individual physical activity/mobility and well-being …
has discussed the relationship between individual physical activity/mobility and well-being …
Data‐Driven Approach for Passenger Mobility Pattern Recognition Using Spatiotemporal Embedding
Urban mobility pattern recognition has great potential in revealing human travel mechanism,
discovering passenger travel purpose, and predicting and managing traffic demand. This …
discovering passenger travel purpose, and predicting and managing traffic demand. This …
CellSense: Human mobility recovery via cellular network data enhancement
Data from the cellular network have been proved as one of the most promising way to
understand large-scale human mobility for various ubiquitous computing applications due to …
understand large-scale human mobility for various ubiquitous computing applications due to …
Understanding Location Privacy of the Point-of-Interest Aggregate Data via Practical Attacks and Defenses
Location-based services have significantly affected mobile users' everyday life, and location
privacy has become essential. Some applications (eg, location-based recommendation …
privacy has become essential. Some applications (eg, location-based recommendation …
Multi-Head Spatio-Temporal Attention Mechanism for Urban Anomaly Event Prediction
Timely forecasting the urban anomaly events in advance is of great importance to the city
management and planning. However, anomaly event prediction is highly challenging due to …
management and planning. However, anomaly event prediction is highly challenging due to …
A Quantitative Approach to Identifying Emergent Editor Roles in Open Street Map
The objective of this study was to investigate and classify the roles, or distinct contribution
styles, adopted by participants within the OpenStreetMap (OSM) community. Using a …
styles, adopted by participants within the OpenStreetMap (OSM) community. Using a …