Results 21 to 30 of about 975 (190)
Next point-of-interest (POI) recommendation provides users with location suggestions that they may be interested in, allowing them to explore their surroundings.
Jiubing Chen +3 more
doaj +1 more source
iTourSPOT: a context-aware framework for next POI recommendation in location-based social networks
The rising prosperity of Location-based Social Networks (LBSNs) witnessed an explosion in the availability of geo-tagged social media data, which enables tremendous location-aware online services, especially next point of interest (POI) recommendation ...
Lin Wan +5 more
doaj +1 more source
Accepted in CIKM ...
Jinsung Jeon +6 more
openaire +2 more sources
Multi-granularity contrastive learning model for next POI recommendation
Next Point-of-Interest (POI) recommendation aims to predict the next POI for users from their historical activities. Existing methods typically rely on location-level POI check-in trajectories to explore user sequential transition patterns, which suffer ...
Yunfeng Zhu, Shuchun Yao, Xun Sun
doaj +1 more source
Research on next-point-of-interest (POI) recommendation has become a new focus in the field of POI recommendation in recent years. The goal of POI recommendation tasks is to predict a user’s future movement trajectory based on their current state and ...
Huarui Yu, Zesheng Cheng
doaj +1 more source
Where To Go at the Next Timestamp
The next Point of Interest (POI) recommendation is the core technology of smart city. Current state-of-the-art models attempt to improve the accuracy of the next POI recommendation by incorporating temporal and spatial intervals or by partitioning the ...
Jiaqi Duan, Xiangfu Meng, Guihong Liu
doaj +1 more source
A Multi-Feature Transition-Aware Framework for Next POI Recommendation
Next Point-of-Interest (POI) recommendation focuses on predicting a user’s subsequent location based on historical check-in data. In practice, however, check-in logs frequently contain uncertain records in which ambiguous spatial, temporal, or behavioral
Oraya Sooknit +2 more
doaj +1 more source
Mapping the “Supply–Demand–Flow” of Ecosystem Services for Ecosystem Management in China
This study develops a “supply–demand–flow” framework clarifies how ecosystem services move between regions by distinguishing potential and actual supply and demand. Using integrated biophysical–socioeconomic modeling, nine services in China were mapped.
Yikun Zhang +3 more
wiley +1 more source
RecPOID: POI Recommendation with Friendship Aware and Deep CNN
In location-based social networks (LBSNs), exploit several key features of points-of-interest (POIs) and users on precise POI recommendation be significant. In this work, a novel POI recommendation pipeline based on the convolutional neural network named
Sadaf Safavi, Mehrdad Jalali
doaj +1 more source
Assessing Household Welfare in Response to Rising Food Prices in The Gambia
ABSTRACT This study examines how rising food prices affected household welfare in The Gambia using nationally representative data from the 2015/16 Integrated Household Survey (IHS‐3). The analysis reflects household consumption behavior and market conditions prevailing during that period and provides a structural benchmark for understanding ...
Roger Vorsah +3 more
wiley +1 more source

