Dear all,
I have just released the SVM-LIGHT-TK1.2 software. This allows us to
describe a classifying object
using a set of trees and a set of vectors in the input of Support Vector
Machines.
Sets of trees are useful to encode different structured features, e.g. it is
possible to select
different portions of a parse tree, independently evaluate tree kernels over
them
and combine the obtained contributions.
Feature Vectors are extremely important to combine different spaces of
manually designed features
and are essential to design SVM models that work on instance pairs (tuples),
e.g. re-ranking models.
The main software features are listed hereafter:
- Fast Kernel computation.
- Tree forests, i.e. a set of trees over multiple feature spaces can be
specified in the input.
- Vector sets, i.e. multiple feature vectors over multiple feature spaces
can be specified in the input.
- Two types of tree kernels, i.e. subset tree and subtree kernels.
- Embedded combinations of tree and vector-based kernels.
- A commented example on how to design our own kernels.
If you are interested, you can read more about the software and download it
here:
http://ai-nlp.info.uniroma2.it/moschitti/Tree-Kernel.htm
I appreciate any bug reports, requests and comments.
Best regards,
Alessandro
--------------------------------------------------------------
Dr. Alessandro Moschitti
Dept. of Computer Science, Systems and Production
University of Rome Tor Vergata
Via del Politecnico 1,
00133 Rome, Italy
tel +39 06 7259 7333
fax +39 06 72597460
e-mail: moschitti@info.uniroma2.it
http://ai-nlp.info.uniroma2.it/moschitti/
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