Abstract
We describe work on automatically inferring the intended meaning of tables and representing it as RDF linked data, making it available for improving search, interoperability and integration. We present implementation details of a joint inference module that uses knowledge from the linked open data (LOD) cloud to jointly infer the semantics of column headers, table cell values (e.g., strings and numbers) and relations between columns. We also implement a novel Semantic Message Passing algorithm which uses LOD knowledge to improve existing message passing schemes. We evaluate our implemented techniques on tables from the Web and Wikipedia.
An extended version of this paper with additional material is available at http://ebiquity.umbc.edu/p/627
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Mulwad, V., Finin, T., Joshi, A. (2013). Semantic Message Passing for Generating Linked Data from Tables. In: Alani, H., et al. The Semantic Web – ISWC 2013. ISWC 2013. Lecture Notes in Computer Science, vol 8218. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41335-3_23
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DOI: https://doi.org/10.1007/978-3-642-41335-3_23
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