Mining Semantic Web data using FastMap - ExampleSet

Created: 2011-06-25 12:11:37      Last updated: 2011-06-25 13:17:51

This workflow describes how to learn from the Semantic Web's data. The input to the workflow is a feature vector developed from a RDF resource.

The loaded example set is then divided into training and test parts. These sub-example sets are used by the FastMap operators (encapsulate the FastMap 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:

Any feedback is really appreciated.

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

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