Automatically Generating Linked Data from Tables
Description: 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.
Authors: Varish Mulwad
Date: November 15, 2011
Format: Microsoft PowerPoint (Need a reader? Get one here)
Number of downloads: 242
Access Control: Publicly Available
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