[ACT-R-users] similarity

[Roman Belavkin]

Hello Ayman,
 
Indeed, Steve Jobs may have a bit different associations than myself, which begs for some explanation, and I think it is beyond a simple difference in the corpus we use. Perhaps term apple, obviously ambiguous, meaning two very different objects, corresponds to two different representations in the mind (i.e. chunks).  And people are able to make this distinction very clearly, whereas a purely text-based technique, such as GLSA (or ICA, LSA, etc) has no means to do it.  Or does it? I wonder if there has been any research on trying to capture this difference with LSA?  Obviously, apple meaning fruit is `similar' to terms such as eat, orange, sweet and red, etc.  While apple meaning mac would have associations with terms such as Steve Jobs, OS X, etc.  The same term belongs to quite different clusters, therefore the method should be able to figure this out.
 
cheers,
Roman

	-----Original Message----- 
	From: act-r-users-admin at act-r.psy.cmu.edu on behalf of Ayman Farahat 
	Sent: Fri 6/17/2005 18:18 
	To: Peter Pirolli; Roy Wilson; act-r-users at act-r.psy.cmu.edu 
	Cc: Raluca.Budiu at parc.com; royer at parc.com 
	Subject: Re: [ACT-R-users] similarity
	
	

	Hello
	The apple example is interesting because it illustrates how the corpus (or
	domain knowledge) can influence similarity.  My feeling is that if we asked
	Steve Jobs (or for that matter a random person in the bay area) about the
	most similar term to apple, MAC would come up very high.
	An interesting example to try is "entropy". You will see that the similarity
	server captures the two senses of the term; the information theory and
	thermodynamics.
	The reason why we get better results with entropy has more to do with the
	corpus than with technique.
	Ayman
	
	> From: Peter Pirolli <pirolli at parc.com>
	> Date: Fri, 17 Jun 2005 09:50:05 PDT
	> To: Roy Wilson <rwilson+ at pitt.edu>, act-r-users at act-r.psy.cmu.edu
	> Cc: Ayman Farahat <farahat at parc.com>, Raluca.Budiu at parc.com, royer at parc.com
	> Subject: Re: [ACT-R-users] similarity
	>
	> As I point out
	> in the Pirolli (2005) Cognitive Science paper, PMI is approximately the
	> same thing as association strength in ACT-R. PMI (like LSA) is very good at
	> generating scores that correlate well with synonym judgements (e.g., as
	> tested by the TOEFL test), which might be one way to define
	
	
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