[Corpora-List] How to word presentation for word clustering?

[Gaël Dias]

Be careful,

IDF is unique for a word and does not depend on the document
so that you have:

vector w = { tf(1)*IDF(w), tf(2)*IDF(w)....,tf(n)*IDF(w))}

Gaël.

Clive De Silva wrote:
> Dear Chen Wenliang,
>
> I am using TF*IDF values as my representation for words.
> vector w = { tf(1)*IDF(1), tf(2)*IDF(2)....,tf(n)*IDF(n))} where the IDF is
> computed from a large corpus. This seems to give better results than just
> the raw frequency counts.
> The representations I investigated were: TF, TF*IDF and simple binary(1
> represents the word existing in the vector and 0 if it isn't) counts.
>
> Regards,
>
> Clive De Silva
> University of Cambridge

--
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Gaël Harry Dias, PhD            | Assistant Professor
Human Language Technology Group | [www.di.ubi.pt/~ddg]
Computer Science Department     | [ddg at di.ubi.pt]
Beira Interior University       | [Tel: +351 275 319 700]
6201-001 - Covilhã - PORTUGAL   | [Fax: +351 275 319 732]
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