Re: [infomap-nlp-users] dimensions

[Beate D. <bea...@gm...>]

Dear James,

I am sending you a slightly modified version of the search/associate.c
program. This new associate.c differs from the one in the infomap package in
that it also accepts a seed *vector* as a query. In order to query for a
vector you have to call associate with the "-q" (for vector) option instead
of "-w" (for words) or "-d" (for documents).
associate expects the vector to take the form of a simple list of SINGVALS
float numbers, where SINGVALS is the dimension of the reduced word space. It
is defined in admin/default_params.in.

To obtain the words most similar to each dimension of the reduced word
space, you can simply call associate -q with the SINGVALS-dimensional
standard basis vectors.

I might have used an old version of the infomap software when I added the -q
option. You may want to run a diff on the two programs. Let me know if you
need further help.

Best wishes,
Beate


2008/3/7, James Evans <je...@uc...>:
>
> Hi,
>
> I don't know if this is still being maintained, but I and my class (I
> teach sociology at the University of Chicago) have found the software
> useful--I was at Stanford when it was developed and knew Dominic
> Widdows.  I was wondering if there is an easy way to print the words
> highest on each of the various dimensions, and the documents highest
> on each dimension.  All of the associate queries are documents and
> words relative to each other...and its not obvious to me how to get
> the complete (or even the ranked) word list relative to each dimension.
>
> Thanks,
>
> james
>
>
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