[Corpora-List] Software release announcement: Tree Kernels and multiple feature vectors in SVM-LIGHT

Alessandro Moschitti moschitti at info.uniroma2.it
Wed Dec 6 16:45:00 CET 2006


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 at info.uniroma2.it
http://ai-nlp.info.uniroma2.it/moschitti/

----- Original Message -----
From: "zhang min" <mzhang at i2r.a-star.edu.sg>
To: "'Alessandro Moschitti'" <moschitti at 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 at lists.uib.no [mailto:owner-corpora at lists.uib.no] On

> Behalf Of Alessandro Moschitti

> Sent: 2006年11月30日 23:24

> To: CORPORA at 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 at info.uniroma2.it

> http://ai-nlp.info.uniroma2.it/moschitti/

>

>

>








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