Duplicate detection in probabilistic data

Abstract— Collected data often contains uncertainties. Probabilistic databases have been proposed to manage uncertain data. To combine data from multiple autonomous probabilistic databases, an integration of probabilistic data has to be performed. Until now, however, data integration approaches have focused on the integration of certain source data (relational or XML). There is no work on the integration of uncertain (esp. probabilistic) source data so far. In this paper, we present a first step towards a concise consolidation of probabilistic data. We focus on duplicate detection as a representative and essential step in an integration process. We present techniques for identifying multiple probabilistic representations of the same real-world entities. Furthermore, for increasing the efficiency of the duplicate detection process we introduce search space reduction methods adapted to probabilistic data.

• Type: Conference
• Year: 2010
• Where: ICDE
• Authors: Fabian Panse, Maurice van Keulen, Ander de Keijzer, Norbert Ritter
• Keywords: Database, ICDE 2010, Probabilistic, Probabilistic Data, Probabilistic Databases