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Title Keyword-Based Navigation and Search over the Linked Data Web
Authors Luca Matteis, Aidan Hogan, Roberto Navigli
Publication date 2015
Abstract Keyword search approaches over RDF graphs have proven
intuitive for users. However, these approaches rely on local copies of RDF
graphs. In this paper, we present an algorithm that uses RDF keyword search
methodologies to find information in the live Linked Data web rather than
against local indexes. Users navigate between documents by specifying
keywords that are matched against triples. Navigation is performed through a
pipeline which streams results to users as soon as they are found. Keyword
search is assisted through the resolution of predicate URIs. We evaluate our
methodology by converting several natural language questions into lists of
keywords and seed URIs. For each question we measured how quickly and how
many triples appeared in the output stream of each step of the pipeline.
Results show that relevant triples are streamed back to users in less than 5
seconds on average. We think that this approach can help people analyze and
explore various Linked Datasets in a follow your nose fashion by simply
typing keywords.
Conference name Linked Data on the Web
Publisher CEUR Publications
Reference URL View reference page