How we can apply dimensionality-reduction technique to a matrix of common-sense knowledge that has been built using RDF/XML e.g. SenticNet 3.?
After converting your data into the appropriate form, you can look at the results by applying PCA or ICA.
In PCA you can reduce size by reducing the variance to a significant degree.
dimensionality-reduction techniques, SenticNet 3 makes use of "energy flows" to connect various parts of extended common and common-sense knowledge representations to one another
Dear Omar,
In addition to PCA and ICA, you may also try to utilize Nonnegative matrix factorization (NMF) technique, which is another method for projecting a data from a higher dimensional space into a lower dimensional space. Thus, reducing the dimension of the original dataset.
I hope you would find this tips helpful.
Best wishes.
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