Similarity and Duplicate Detection System for an OAI Compliant Federated Digital Library

Abstract

The Open Archives Initiative (OAI) is making feasible to build high level services such as a federated search service that harvests metadata from different data providers using the OAI protocol for metadata harvesting (OAI-PMH) and provides a unified search interface. There are numerous challenges to build and maintain a federation service, and one of them is managing duplicates. Detecting exact duplicates where two records have identical set of metadata fields is straight-forward. The problem arises when two or more records differ slightly due to data entry errors, for example. Many duplicate detection algorithms exist, but are computationally intensive for large federated digital library. In this paper, we propose an efficient duplication detection algorithm for a large federated digital library like Arc.