  Vacant lots are neglected properties in a city that lead to environmental
hazards and poor standard of living for the community. Thus, reclaiming vacant
lots and putting them to productive use is an important consideration for many
cities. Given a large number of vacant lots and resource constraints for
conversion, two key questions for a city are (1) whether to convert a vacant
lot or not; and (2) what to convert a vacant lot as. We seek to provide
computational support to answer these questions. To this end, we identify the
determinants of a vacant lot conversion and build a recommender based on those
determinants. We evaluate our models on real-world vacant lot datasets from the
US cities of Philadelphia,PA and Baltimore, MD. Our results indicate that our
recommender yields mean F-measures of (1) 90% in predicting whether a vacant
lot should be converted or not within a single city, (2) 91% in predicting what
a vacant lot should be converted to, within a single city and, (3) 85% in
predicting whether a vacant lot should be converted or not across two cities.
