Using open information extraction and linked open data towards ontology enrichment and alignment

Abstract

The interlinking, maintenance and updating of different Linked Data repositories is steadily becoming a critical issue as the amount of published data increases. The wealth of information across the World Wide Web can be exploited in order to provide additional information about the way that an object is described in the real world. This paper proposes a method for discovering new concepts and examining the equivalence of properties in different LOD description schemas by using Open Information Extraction techniques on web resources. The method relies on constructing association graphs from the extracted information, proceeding to a transfer on the conceptual level using information previously known from the LOD repositories and examining the similarities and discrepancies between the produced graphs and the LOD descriptions, as well as between the graphs derived from different repositories. © 2012 Springer-Verlag.