Thanks Ted, Amruta. There are lots of ways to define features for a problem like this. I see you support a number of them. I'm not sure if you support mine.
I have a kind of context "frame". For instance, given a text fragment <context>A<head>X</head>B</context> my feature would be A_B, where A, B, and X can be ngrams in general (but in practice I've only used ngrams for the token X because ngram context "frames" become way too specific = rare). What I'm wondering is if "locking" the prior and following contexts (A and B) together like this (context features A and B become single context feature A_B) will give a different result to simply including prior and following context A and B in the context vector without reference to each other (which I now understand is possible with your package). I haven't tried this (unlocked), but I did find that it was necessary to have prior and following context to distinguish ngram tokens. The other question is have you considered combining 1st order and 2nd order processing. If your 2nd order processing can be taken as similar to mine, and I think it can, then it increases generality nicely, but also decreases reliability. I have been exploring ways of using both 1st order and 2nd order stats. with the 2nd order stats. scaled appropriately to reflect their lower reliability. What I am really trying to find out is if you would profit from looking at my code for this problem. Alternatively I would like to know if I could use your code to produce word similarity "vectors" usable by my parsing algorithm. My main interest is to improve my word similarity vectors (e.g. http://www.collectivelanguage.com/cgi-bin/engword.cgi?word=a+word) so that I can increase my parsing accuracy. My word similarity vectors are like the rows or columns of your similarity matrix, I think. -Rob ------------------------------------------------------- This SF.net email is sponsored by: Perforce Software. Perforce is the Fast Software Configuration Management System offering advanced branching capabilities and atomic changes on 50+ platforms. Free Eval! http://www.perforce.com/perforce/loadprog.html _______________________________________________ senseclusters-users mailing list [EMAIL PROTECTED] https://lists.sourceforge.net/lists/listinfo/senseclusters-users
