Point-of-interest demand modeling with human mobility patterns
Point-of-Interest (POI) demand modeling in urban regions is critical for many applications
such as business site selection and real estate investment. While some efforts have been …
such as business site selection and real estate investment. While some efforts have been …
Urban point-of-interest recommendation by mining user check-in behaviors
In recent years, researches on recommendation of urban Points-Of-Interest (POI), such as
restaurants, based on social information have attracted a lot of attention. Although a number …
restaurants, based on social information have attracted a lot of attention. Although a number …
Modelling of bi-directional spatio-temporal dependence and users' dynamic preferences for missing poi check-in identification
Human mobility data accumulated from Point-of-Interest (POI) check-ins provides great
opportunity for user behavior understanding. However, data quality issues (eg, geolocation …
opportunity for user behavior understanding. However, data quality issues (eg, geolocation …
Exploiting human mobility patterns for point-of-interest recommendation
Z Yao - Proceedings of the Eleventh ACM International …, 2018 - dl.acm.org
Point-of-interest (POI) recommendation, which provides personalized recommendation of
places to mobile users, is an important task in location-based social networks (LBSNs) …
places to mobile users, is an important task in location-based social networks (LBSNs) …
Adapting to user interest drift for poi recommendation
Point-of-Interest recommendation is an essential means to help people discover attractive
locations, especially when people travel out of town or to unfamiliar regions. While a …
locations, especially when people travel out of town or to unfamiliar regions. While a …
Transfer urban human mobility via poi embedding over multiple cities
Rapidly developing location acquisition technologies provide a powerful tool for
understanding and predicting human mobility in cities, which is very significant for urban …
understanding and predicting human mobility in cities, which is very significant for urban …
[HTML][HTML] Mining point-of-interest data from social networks for urban land use classification and disaggregation
Over the last few years, much online volunteered geographic information (VGI) has emerged
and has been increasingly analyzed to understand places and cities, as well as human …
and has been increasingly analyzed to understand places and cities, as well as human …
Discovering regions of different functions in a city using human mobility and POIs
The development of a city gradually fosters different functional regions, such as educational
areas and business districts. In this paper, we propose a framework (titled DRoF) that …
areas and business districts. In this paper, we propose a framework (titled DRoF) that …
Learning from hometown and current city: Cross-city POI recommendation via interest drift and transfer learning
With more and more frequent population movement between different cities, like users' travel
or business trip, recommending personalized cross-city Point-of-Interests (POIs) for these …
or business trip, recommending personalized cross-city Point-of-Interests (POIs) for these …
Where have you been: Dual spatiotemporal-aware user mobility modeling for missing check-in POI identification
The prevalence of Location-based Social Networks (LBSNs) services makes next
personalized Point-of-Interest (POI) predictions become a trending research topic. However …
personalized Point-of-Interest (POI) predictions become a trending research topic. However …