Improving record matching in imprecise and uncertain datasets

Museum collections represent a highly challenging search space. This article proposes a novel approach for co-referent record identification which is suitable for use across multiple separate collections. The proposed approach is intended to be suitable for use despite highly imprecise/uncertain attribute values in the records. It is hoped that this can be achieved through a combination of aspects from the fields of probabillistic record linkage, document classification, and fuzzy clustering.