State of the art on quality control for data streams: A systematic literature review
These days, endless streams of data are generated by various sources such as sensors,
applications, users, etc. Due to possible issues in sources, such as malfunctions in sensors …
applications, users, etc. Due to possible issues in sources, such as malfunctions in sensors …
[HTML][HTML] MiPo: How to detect trajectory outliers with tabular outlier detectors
J Yang, X Tan, S Rahardja - Remote sensing, 2022 - mdpi.com
Trajectory outlier detection is one of the fundamental data mining techniques used to
analyze the trajectory data of the Global Positioning System. A comprehensive literature …
analyze the trajectory data of the Global Positioning System. A comprehensive literature …
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 …
A convex-programming approach for efficient directed densest subgraph discovery
Given a directed graph G, the directed densest subgraph (DDS) problem refers to finding a
subgraph from G, whose density is the highest among all subgraphs of G. The DDS problem …
subgraph from G, whose density is the highest among all subgraphs of G. The DDS problem …
Deep learning for trajectory data management and mining: A survey and beyond
Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …
mining, garnering widespread attention due to its crucial role in various practical …
Micro-Macro Spatial-Temporal Graph-Based Encoder-Decoder for Map-Constrained Trajectory Recovery
Recovering intermediate missing GPS points in a sparse trajectory, while adhering to the
constraints of the road network, could offer deep insights into users' moving behaviors in …
constraints of the road network, could offer deep insights into users' moving behaviors in …
Lightpath: Lightweight and scalable path representation learning
Movement paths are used widely in intelligent transportation and smart city applications. To
serve such applications, path representation learning aims to provide compact …
serve such applications, path representation learning aims to provide compact …
Origin-destination travel time oracle for map-based services
Given an origin (O), a destination (D), and a departure time (T), an Origin-Destination (OD)
travel time oracle~(ODT-Oracle) returns an estimate of the time it takes to travel from O to D …
travel time oracle~(ODT-Oracle) returns an estimate of the time it takes to travel from O to D …
Finding locally densest subgraphs: a convex programming approach
Finding the densest subgraph (DS) from a graph is a fundamental problem in graph
databases. The DS obtained, which reveals closely related entities, has been found to be …
databases. The DS obtained, which reveals closely related entities, has been found to be …
Accelerating directed densest subgraph queries with software and hardware approaches
Given a directed graph G, the directed densest subgraph (DDS) problem refers to finding a
subgraph from G, whose density is the highest among all subgraphs of G. The DDS problem …
subgraph from G, whose density is the highest among all subgraphs of G. The DDS problem …