Mining Semantic Web data using Correspondence Analysis - Read RDF

Created: 2011-06-25 14:48:59      Last updated: 2011-06-25 15:01:59

This workflow will explain that how an example set can be extracted from an RDF resource using the provided SPARQL query.

This example set is then divided into training and test parts. These sub-example sets are used by the Correspondencce Analysis operators (encapsulate the Correspondencce Analysis data transformation technique) which processes each feature at a time and transform the data into a different space. This transformed data is more meaningful and helps the learner to improve classfication peformance. The tranformed data and the calculated distance matrices can be observed using Distance Matrix operator, which gives a better understanding of underlying process.

Please visit the following URL to download the released plugin together with code and relevant documentation:

Looking forward for the feedback

Information Preview

Information Run

Not available

Information Workflow Components


Information Workflow Type


Information Uploader

Information License

All versions of this Workflow are licensed under:

Information Version 1 (of 1)

Information Credits (0)



Information Attributions (0)



Information Tags (7)

Log in to add Tags

Information Shared with Groups (0)


Information Featured In Packs (0)


Log in to add to one of your Packs

Information Attributed By (0)



Information Favourited By (0)

No one

Information Statistics


Citations (1)

1. Mansoor Khan, Gunnar Grimnes, Andreas Dengel, Two pre-processing operators for improved learning from SemanticWeb data, RCOM2010, 13 September 2010,

Version History

In chronological order:

Reviews Reviews (0)

No reviews yet

Be the first to review!

Comments Comments (0)

No comments yet

Log in to make a comment

Workflow Other workflows that use similar services (0)

There are no workflows in myExperiment that use similar services to this Workflow.