Hi Min,
sorry for the delayed answer and
thank you to verify the consistency of the kernel description.
The question was
"in your website, in equation K_all(O_1,O_2) as below, it
seems that the loop range of j should be [1,n’] rather than [I,n’]. Is it?
"
You are in right, it is a typo. In the source code the loop range is the one
that you have told. When I was
describing it in the web page I made a mistake.
Cheers
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/
----- Original Message -----
From: "zhang min" <mzhang@i2r.a-star.edu.sg>
To: "'Alessandro Moschitti'" <moschitti@info.uniroma2.it>
Sent: Friday, December 01, 2006 3:07 AM
Subject: RE: [Corpora-List] Software release announcement: Tree Kernels
andmultiple feature vectors in SVM-LIGHT
>
> Hi, Alessandro,
>
> Congratulations for the new tool release with many new features.
>
> I believe the research community will benefit from it.
>
>
> One small question, in your website, in equation K_all(O_1,O_2) as below,
> it
> seems that the loop rang of j shoul be [1,n’] rather than [I,n’]. Is it?
>
>
> Cheers,
>
> Zhang Min
>
>
>
>
> -----Original Message-----
> From: owner-corpora@lists.uib.no [mailto:owner-corpora@lists.uib.no] On
> Behalf Of Alessandro Moschitti
> Sent: 2006年11月30日 23:24
> To: CORPORA@UIB.NO
> Subject: [Corpora-List] Software release announcement: Tree Kernels
> andmultiple feature vectors in SVM-LIGHT
>
> 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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