02_​OCR_​meets_​SemanticWeb

0 ×

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?

Nodes

• Column Rename4 ×
• Component Input4 ×
• Component Output4 ×
• Joiner4 ×
• Constant Value Column3 ×
• Show all 38 nodes

Extensions

• FeatureKNIME Base nodes
• FeatureKNIME Image Processing
• FeatureKNIME Image Processing - Tess4J Integration
• FeatureKNIME JavaScript Views
• FeatureKNIME Javasnippet
• Show all 7 modules

Links

• OCR meets Semantic Web - Natural Selection vs Modern Theory

  www.knime.org/blog/OCR-meets-SemanticWeb