Work

Noise-Aware Explanatory Enrichment of Origin–Destination Frequency Tensors for Interpretable Mobility Clustering

Year: 2026

Type: article

Abstract: This paper proposes a noise-aware, iterative methodology for enriching an initial mobility clustering through the sequential addition of explanatory variables. The framework separates one-off density-based cluster discovery from scalable characterisation over a fixed analytical population. Candidate variables are retained only when they improve the predefined distributional criteria and preserve continuity with the latest accepted partition. Evaluation on a large sensing-based mobility dataset from Valencia shows that the proposed architecture supports scalable and auditable explanatory enrichment while keeping the observation set unchanged and explicitly separating distributional admissibility from inter-partition continuity.

Source: Sensors

DOI: 10.3390/s26216999

Authors: Dani Marchuet, Javi Palanca, Vicent Botti

Institution: Universitat Politècnica de València

Language: English

Topic: Human Mobility and Location-Based Analysis

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $3,137