activity
20232026
most citedNeural Collaborative Filtering to Detect Anomalies in Human Semantic Trajectories

2 citations · 3 across the 14 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG2026

Staypoint Detection from Noisy Trajectory Data [Experiment Paper]

Lance Kennedy, Hossein Amiri, Yueyang Liu +9

Detecting staypoints from raw trajectory data is fundamental to numerous spatial computing applications. This process transforms raw numeric sequences of geolocations into semantic…

cs.LG2025

PlaceRep: Geospatial Place Representation Learning from Large-Scale Point-of-Interest Data

Mohammad Hashemi, Hossein Amiri, Andreas Zufle

Learning effective representations of urban environments requires capturing spatial structure beyond fixed administrative boundaries. Existing geospatial representation learning ap…

cs.LG2024

Transferable Unsupervised Outlier Detection Framework for Human Semantic Trajectories

Zheng Zhang, Hossein Amiri, Dazhou Yu +3

Semantic trajectories, which enrich spatial-temporal data with textual information such as trip purposes or location activities, are key for identifying outlier behaviors critical…

cs.LG2024★ 2 cited

Neural Collaborative Filtering to Detect Anomalies in Human Semantic Trajectories

Yueyang Liu, Lance Kennedy, Hossein Amiri +1

Human trajectory anomaly detection has become increasingly important across a wide range of applications, including security surveillance and public health. However, existing traje…

cs.LG2023★ 1 cited

Large Language Models for Spatial Trajectory Patterns Mining

Zheng Zhang, Hossein Amiri, Zhenke Liu +2

Identifying anomalous human spatial trajectory patterns can indicate dynamic changes in mobility behavior with applications in domains like infectious disease monitoring and elderl…