OCR meets SemanticWeb

The challenge here is to blend Semantic Web data and image data (in PNG format) by implementing dbpedia queries using SPARQL query language and by using Optical Character Recognition (OCR). The goal is to find differences in the content between the Natural Selection theory developed by Charles Darwin and the new modern evolutionary theories. The evolutionary idea proposed by Charles Darwin and called "Natural selection theory" explains the mechanisms of evolution. It is featured in his book "Origin of Species" which, for this workflow, is available through .png files. On the other side, the new modern evolutionary synthesis theory has been queried with SPARQL Query nodes. After some text pre-processing, two different tag clouds graphically show the terms occurring in both sources (the book "Origin of Species" and the content queried from dbpedia related to modern evolutionary synthesis theory)Will they blend?

OCR meets SemanticWeb



EXAMPLES Server: 99_Community/01_Image_Processing/02_Integrations/03_Tess4J/02_OCR_meets_SemanticWeb99_Community/01_Image_Processing/02_Integrations/03_Tess4J/02_OCR_meets_SemanticWeb*
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* Find more about the Examples Server here.
The link will open the workflow directly in KNIME Analytics Platform (requirements: Windows; KNIME Analytics Platform must be installed with the Installer version 3.2.0 or higher). In other cases, please use the link to a zip-archive or open the provided path manually