Beyond 100 million entities: large-scale blocking-based resolution for heterogeneous data

A prerequisite for leveraging the vast amount of data available on the Web is Entity Resolution, i.e., the process of identifying and linking data that describe the same real-world objects. To make this inherently quadratic process applicable to large data sets, blocking is typically employed: entities (records) are grouped into clusters - the blocks - of matching candidates and only entities of the same block are compared. However, novel blocking techniques are required for dealing with the noisy, heterogeneous, semi-structured, user-generated data in the Web, as traditional blocking techniques are inapplicable due to their reliance on schema information. The

• Type: Journal
• Year: 2012
• Where: WSDM
• Authors: George Papadakis, Ekaterini Ioannou, Claudia Niederée, Themis Palpanas, Wolfgang Nejdl
• Keywords: Clusters, Data Mining, Linking Data, Prerequisite, WSDM 2012