Efficient Semantic-Aware Detection of Near Duplicate Resources

Ekaterini Ioannou, Odysseas Papapetrou, Dimitrios Skoutas, Wolfgang Nejdl
L3S Research Center, University of Hannover

{ioannou, papapetrou, skoutas, nejdl}@L3S.de

Abstract: Elsevierciently detecting near duplicate resources is an important task when integrating information from various sources and applications. Once detected, near duplicate resources can be grouped together, merged, or removed, in order to avoid repetition and redundancy, and to increase the diversity in the information provided to the user. In this paper, we introduce an approach for efficientcient semantic-aware near duplicate detection, by combining an indexing scheme for similarity search with the RDF representations of the resources.We provide a probabilistic analysis for the correctness of the suggested approach, which allows applications to configure it for satisfying their specific quality requirements. Our experimental evaluation on the RDF descriptions of real-world news articles from various news agencies demonstrates the efficientciency and effectiveness of our approach.

To appear in: ESWC 2010