On Tue, Dec 13, 2005 at 10:53:42AM +0000, adasal wrote: > There seem to be quite a few alternatives around. I would be interested in > comments on the following:- > The work at NITLE <http://www.nitle.org/tools/semantic/search.htm> > using Contextual > Network Search (CNS) a graph-based alternative to LSI.
Hi, perhaps I can say a few words about CNS. I evaluated spreading activation search (which is what CNS is based on) for my master's thesis. I must conclude that SA is a rather fickle method -- if you read Preece's thesis, you will see that it can be used to implement a number of retrieval algorithms and techniques. The devil is in the details: SA depends strongly on a suitable set of adjustments and constraints which express exactly the kind of retrieval (or inference) algorithm you want. For applications of SA in Retrieval, see for example the following publications: http://www.sebastian-kirsch.org/moebius/reading.html#Crestani1997a http://www.sebastian-kirsch.org/moebius/reading.html#Crestani2000 http://www.sebastian-kirsch.org/moebius/reading.html#Belew1989 http://www.sebastian-kirsch.org/moebius/reading.html#Pirolli1996 You will notice that Crestani stresses the fact that no successful commercial system based on SA was ever produced. I am also unaware of any peer-reviewed publications on CNS, or follow-up publications by NITLE. Maciej Ceglowski has since left NITLE, as far as I know. So if I was you, I'd place my bet on probabilistic or linear algebra methods like pLSI/LSI. If anyone wants to chime in, please feel free to comment ;) Regards, Sebastian -- Sebastian Kirsch <[EMAIL PROTECTED]> [http://www.sebastian-kirsch.org/] NOTE: New email address! Please update your address book. --------------------------------------------------------------------- To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
