2012/02/14 by David Mimno, Mimno, David
Arts and Humanities · Computer Science · Mathematics · #Ancient Mediterranean Archaeology and History #FOS: Computer and information sciences #Image Processing and 3D Reconstruction #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Music and Audio Processing #cs.LG #stat.ML
paper · pdf · doi:10.48550/arxiv.1202.3747
arxiv created 2012/02/14 · openalex publication_date 2012/02/14 · arxiv updated 2012/02/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A database of objects discovered in houses in the Roman city of Pompeii provides a unique view of ordinary life in an ancient city. Experts have used this collection to study the structure of Roman households, exploring the distribution and variability of tasks in architectural spaces, but such approaches are necessarily affected by modern cultural assumptions. In this study we present a data-driven approach to household archeology, treating it as an unsupervised labeling problem. This approach scales to large data sets and provides a more objective complement to human interpretation.