Random indexing for finding similar nodes within large RDF graphs

Authors:
Danica Damljanovic;Johann Petrak;Mihai Lupu;Hamish Cunningham;Mats Carlsson;Gunnar Engstrom;Bo Andersson
Affiliations:
Department of Computer Science, University of Sheffield, United Kingdom;Austrian Research Institute for Artificial Intelligence, Vienna, Austria;Information Retrieval Facility (IRF), Vienna, Austria;Department of Computer Science, University of Sheffield, United Kingdom;AstraZeneca, Lund, Sweden;AstraZeneca, Lund, Sweden;AstraZeneca, Lund, Sweden
Venue:
ESWC'11 Proceedings of the 8th international conference on The Semantic Web
Year:
2011

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Abstract

We propose an approach for searching large RDF graphs, using advanced vector space models, and in particular, Random Indexing (RI). We first generate documents from an RDF Graph, and then index them using RI in order to generate a semantic index, which is then used to find similarities between graph nodes. We have experimented with large RDF graphs in the domain of life sciences and engaged the domain experts in two stages: firstly, to generate a set of keywords of interest to them, and secondly to judge on the quality of the output of the Random Indexing method, which generated a set of similar terms (literals and URIs) for each keyword of interest.