Hme: A hyperbolic metric embedding approach for next-poi recommendation
With the increasing popularity of location-aware social media services, next-Point-of-Interest
(POI) recommendation has gained significant research interest. The key challenge of next …
(POI) recommendation has gained significant research interest. The key challenge of next …
Alleviating data sparsity problem in time-aware recommender systems using a reliable rating profile enrichment approach
Recommender systems use intelligent algorithms to learn a user's preferences and provide
them relevant suggestions. Lack of sufficient ratings–also known as data sparsity problem …
them relevant suggestions. Lack of sufficient ratings–also known as data sparsity problem …
Self-supervised representation learning for geographical data—A systematic literature review
Self-supervised representation learning (SSRL) concerns the problem of learning a useful
data representation without the requirement for labelled or annotated data. This …
data representation without the requirement for labelled or annotated data. This …
Deep trajectory recovery with fine-grained calibration using kalman filter
With the development of location-acquisition technologies, there are a huge number of
mobile trajectories generated and accumulated in a variety of domains. However, due to the …
mobile trajectories generated and accumulated in a variety of domains. However, due to the …
Self-supervised contrastive representation learning for large-scale trajectories
Trajectory representation learning aims to embed trajectory sequences into fixed-length
vector representations while preserving their original spatio-temporal feature proximity …
vector representations while preserving their original spatio-temporal feature proximity …
From motion activity to geo-embeddings: Generating and exploring vector representations of locations, traces and visitors through large-scale mobility data
A Crivellari, E Beinat - ISPRS International Journal of Geo-Information, 2019 - mdpi.com
The rapid growth of positioning technology allows tracking motion between places, making
trajectory recordings an important source of information about place connectivity, as they …
trajectory recordings an important source of information about place connectivity, as they …
MARC: a robust method for multiple-aspect trajectory classification via space, time, and semantic embeddings
The increasing popularity of Location-Based Social Networks (LBSNs) and the semantic
enrichment of mobility data in several contexts in the last years has led to the generation of …
enrichment of mobility data in several contexts in the last years has led to the generation of …
Anomalous trajectory detection using recurrent neural network
Anomalous trajectory detection which plays an important role in taxi fraud detection and
trajectory data preprocessing is a crucial task in trajectory mining fields. Traditional …
trajectory data preprocessing is a crucial task in trajectory mining fields. Traditional …
Location data analytics in the business value chain: A systematic literature review
Context information has become a significant asset to optimize the value obtained from
information systems. Location is an important type of context information that refers to the …
information systems. Location is an important type of context information that refers to the …
An attention-based spatiotemporal GGNN for next POI recommendation
Q Li, X Xu, X Liu, Q Chen - IEEE Access, 2022 - ieeexplore.ieee.org
The task of Point-of-Interest (POI) recommendation is to recommend the next interest
locations for users. Gated Graph Neural Network (GGNN) has been proved to be effective on …
locations for users. Gated Graph Neural Network (GGNN) has been proved to be effective on …