Talk:Spreading activation

message: Is the "fan out effect" the same as the fan effect? Earcanal (talk) 17:44, 4 April 2015 (UTC)
thread_title:  Fan effect 

message: The Texai link doesn't lead to an open source project, but a company. Maybe there is an error.  — Preceding unsigned comment added by 193.204.59.75 (talk) 14:35, 28 May 2014 (UTC)
thread_title:  Check links 

message: The formal description is faulty as usual. For example, the activation level is in [0,1], but the algorithm presented may activate nodes to more than 1.0 There are other problems. The only sound descriptions I know are Anderson 1983 and my own PhD diss. My diss. also contains a comparison with Markov chains. When I have time I'll try to improve this article. Others please feel free. My diss. can be found here is here: https://www.box.com/shared/static/m4f8icz86m3dkv7r9dpa.pdf
Marius63 (talk) 11:39, 11 July 2013 (UTC)
thread_title:  This is wrong, Anderson and myself are right. Markov chains 

message: Also these papers are relevant to SA and Semantic Web:
 
http://portal.acm.org/citation.cfm?id=988723
www.waset.org/ijcs/v1/v1-3-30.pdf
I need to improve the formatting of the formulas using TeX Help:Displaying a formula 
User:StephenReed 21:53, 25 March 2008 (UTC)
thread_title:  Other papers 

message: The spreading activation algorithm, as described in this article, appears to be similar to a Markov chain, and, based on my current reading/misunderstanding of this article, appears to be almost identical, except for various odd tweaks (like the minimal F to fire).  To be precise, if W_{ij} is the weight matrix from this article, and R is the decay factor from this article, then, from what I can tell,
:p_{ij} = \delta_{ij} + RW_{ij}
seems to give a very nearly equivalent Markov chain. (Although the p_{ij}, as I wrote it here, is mis-normalized, which might be why the activation of the neurons needs to be clamped to zero, one, since this mis-normalization will propagate through. Proper normalization wouldn't require clamping). FWIW, the symbol \delta_{ij} is the Kronecker delta function.
To summarize: the only differences I can spot are: 
*Use of the minimal firing factor F
*Clamping (which wouldn't be needed if the system was normalized)
Am I missing something else? I ask, because these two differences alone, although they alter the Markov chain result somewhat, really wouldn't make much of a qualitative difference. And if there's no qualtitative difference, it begs the question: why bother with this (what would the theoretical reasons be?) as opposed to the far-more-widely-known, better-understood Markov chain? linas (talk) 15:36, 30 September 2008 (UTC)
thread_title:  Relation to Markov chain? 

message: This is super pedantic, but I think one of the numbers in the figure example is wrong.
I think the activation on node2 should be 0.765, i.e. 77% not 76%.
Also, there is no mention of the firing threshold in this example.
Cai (talk) 18:18, 6 February 2018 (UTC)
thread_title:  Example figure issues 

message: There is a lack of clarity with the algorithm section.
For example, it does not state at what point the nodes "marked for firing on the next … cycle" will actually fire.
It also does not specify whether a node [j] in step 3 must be unfired.
I would update it myself, but there is no citation given for the algorithm.
Cai (talk) 18:25, 6 February 2018 (UTC)
thread_title:  Algorithm section unclear