Conflating point of interest (POI) data: A systematic review of matching methods

K Sun, Y Hu, Y Ma, RZ Zhou, Y Zhu - Computers, Environment and Urban …, 2023 - Elsevier
Point of interest (POI) data provide digital representations of places in the real world, and
have been increasingly used to understand human-place interactions, support urban …

Activity-travel pattern inference based on multi-source big data

X Fu, Y Zhang, JD Ortúzar, G Lü - Transport Reviews, 2025 - Taylor & Francis
We provide a comprehensive review of the literature on inferring activity-travel patterns
(ATP) using multi-source big data; the increasing number of publications over time on this …

Estimation of trip purposes in public transport during the COVID-19 pandemic: The case of Santiago, Chile

R Pezoa, F Basso, P Quilodrán, M Varas - Journal of Transport Geography, 2023 - Elsevier
The COVID-19 pandemic strongly affected the mobility of people. Several studies have
quantified these changes, for example, measuring the effectiveness of quarantine measures …

A bus passenger flow prediction model fused with point-of-interest data based on extreme gradient boosting

W Lv, Y Lv, Q Ouyang, Y Ren - Applied Sciences, 2022 - mdpi.com
Bus operation scheduling is closely related to passenger flow. Accurate bus passenger flow
prediction can help improve urban bus planning and service quality and reduce the cost of …

[HTML][HTML] Unveiling mobility patterns beyond home/work activities: A topic modeling approach using transit smart card and land-use data

N Aminpour, S Saidi - Travel Behaviour and Society, 2025 - Elsevier
In this paper, a probabilistic topic modeling algorithm called Latent Dirichlet Allocation (LDA)
is implemented to infer trip purposes from activity attributes revealed from smart card transit …

Spatio-temporal intention learning for recommendation of next point-of-interest

H Li, P Yue, S Li, C Zhang, C Yang - Geo-spatial Information …, 2024 - Taylor & Francis
Next point-of-interest (POI) recommendation has been applied by many internet companies
to enhance the user travel experience. Recent research advocates deep-learning methods …

Delineating Urban Community Life Circles for Large Chinese Cities Based on Mobile Phone Data and POI Data—The Case of Wuhan

H Jiao, M **ao - ISPRS International Journal of Geo-Information, 2022 - mdpi.com
In the recent decade, a new concept, urban community life circle (CLC), has been
introduced and widely applied to Chinese community planning and public service facilities …

Differences in Urban Development in China from the Perspective of Point of Interest Spatial Co-Occurrence Patterns

G Dong, R Li, F Li, Z Liu, H Wu, L **ang, W Yu… - … International Journal of …, 2024 - mdpi.com
An imbalance in urban development in China has become a contradiction. Points of Interest
(POIs) serve as representations of the spatial distribution of urban functions. Analyzing POI …

Activity type detection of mobile phone data based on self-training: Application of the teacher–student cycling model

L Gao, H Huang, J Ye, D Wang - Transportation research part C: emerging …, 2024 - Elsevier
Incorporating mobile phone data, known for its high spatial and temporal resolution and
extensive population coverage, into Activity-Based Models (ABM) for understanding …

CIAM: A data-driven approach for classifying long-term engagement of public transport riders at multiple temporal scales

R Cardell-Oliver, D Olaru - Transportation Research Part A: Policy and …, 2022 - Elsevier
Many human activities, including daily travel, show a mix of stable, intermittent and changing
patterns in demand by individuals over time. However, the lack of continuous, long-term …