Harnessing spatio-temporal patterns in data for nominal attribute imputation

Abstract

Missing data in Volunteered Geographic Information (VGI) are an unavoidable consequence of data collection by non-experts, guided by only vague and informal mapping guidelines. While various Missing Value Imputation (MVI) techniques have been proposed as data cleansing strategies, they have primarily targeted numerical data attributes in non-spatial databases. There remains a significant gap in methods for imputing nominal attribute values (e.g., Street Name) in map databases. Here, we present an imputation algorithm called the Membership Imputation Algorithm (MIA), targeting spatial databases and enabling imputation of nominal values in spatially referenced records. By targeting membership ..