  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.
