[SPAM: 4.500] RE: [ACT-R-users] ACT-R output from GLSA server at PARC

[Roman Belavkin]

Hi,
 
I think the word `similar' is not really appropriate here.  LSA just shows co-occurance of the two words really, and higher co-occurance for word man can be simply explained because the word man means also human, while woman is more specific and thus less ambiguous.
 
Cheers,
Roman

	-----Original Message----- 
	From: act-r-users-admin at act-r.psy.cmu.edu on behalf of Kelley, Troy (Civ,ARL/HRED) 
	Sent: Thu 6/9/2005 21:52 
	To: act-r-users at act-r.psy.cmu.edu 
	Cc: 
	Subject: [SPAM: 4.500] RE: [ACT-R-users] ACT-R output from GLSA server at PARC
	
	

	Here is a sample output from the GLSA server at PARC for the word Love 

	love    love    0.9999997 
	love    fun     0.16717705 
	love    city    0.103955254 
	love    place   0.2078263 
	love    man     0.36086833 
	love    friend  0.19896048 
	love    neighbor        -0.037641484 
	love    woman   0.21863273 
	love    fondness        0.0076576206 

	Interesting, love is more similar to the word "man" than "woman", and 
	more similar to "man" than "fondness" or "friend". 

	Troy 

	-----Original Message----- 
	From: act-r-users-admin at act-r.psy.cmu.edu 
	[mailto:act-r-users-admin at act-r.psy.cmu.edu] On Behalf Of 
	Raluca.Budiu at parc.com 
	Sent: Thursday, June 09, 2005 3:54 PM 
	To: act-r-users at act-r.psy.cmu.edu 
	Subject: [ACT-R-users] ACT-R output from GLSA server at PARC 



	Some of you may have heard about PARC's effort to build an external 
	GLSA/PMI server; it is now available at: 

	http://glsa.parc.com/ 

	and it produces ACT-R output (other formats are supported as well). 

	GLSA (Generalized Latent Semantic Analysis) is a LSA-like method of 
	computing word similarities, but  it has the advantage of an adjustable, 
	web-based corpus. It takes as input a list of word pairs and provides 
	similarities between those words. 

	Just very recently it started providing ACT-R output; this is an  ACT-R 
	file that defines a meaning chunk type and sets the Sij-s between words 
	to their similarity value as computed by the server.  

	The server is still in a development phase, but please feel free to 
	experiment with it. Comments and suggestions are very welcome. 

	Raluca Budiu 

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