Automatically Generating Linked Data from Tables

Varish Mulwad

November 15, 2011

2507147 bytes

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learning, semantic web

Evidence for a table’s meaning can be found in its metadata but currently requires human interpretation. We describe techniques grounded in graphical models and probabilistic reasoning to infer meaning associated with a table. Using background knowledge from the Linked Open Data cloud, we automatically infer the semantics of column headers, table cell values (e.g., strings and numbers) and relations between columns and represent the inferred meaning as graph of RDF triples.



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Past Projects

  1. Tables to Linked Data


  1. (Event) Semantic Web Meetup has PowerPoint slides (Resource) Automatically Generating Linked Data from Tables