Property Classification of Vacation Rental Properties during Covid-19
Aghaebe, Favour Yahdii, Foley, Dustin, Atwell, Eric, Clark, Stephen
–arXiv.org Artificial Intelligence
University of Leeds GISRUK 2024 Summary This abstract advocates for employing clustering techniques to classify vacation rental properties active during the Covid pandemic to identify inherent patterns and behaviours . The dataset, a collaboration betwee n the ESRC funded Consumer Data Research Centre (CDRC) and AirDNA, encompasses data for over a million properties and hosts. Utili s ing K - means and K - medoids clustering techniques, we identify homogenous groups and their common characteristics. Our findings enhance comprehension of the intricacies of vacation rental evaluations and could potentially be utilised in the creation of targeted, cluster - specific policies. KEYWORDS: Covid - 19, Hospitality, Clustering, Unsupervised Machine Learnin g 1. Introduction Travel and tourism ha ve been embedded into our human experience for centuries.
arXiv.org Artificial Intelligence
Oct-10-2025
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