Hi.
I am looking for technical papers and/or code for a simple form of linguistic pattern recognition, specifically, that for finite automata.
For finite automata the solution to constructing minimal automaton based on queries is known under the name of Angluin's algorithm. The original paper of Dana Angluin does not seem to be online, but can be found in most books about machine learning. Online you can look at many of the subsequent improvements, e.g. a parallel algorithm: http://www.jukm.org/jucs_2_3/an_optimal_parallel_algorithm/Balcazar_J_L.pdf
So what's the state of the art for NLP, then?
Well, of course there is a lot going on. One wide branch is statistical learning (learning is sometimes called grammar induction, just a tip for googling), another way is to look at it in a more logic-oriented fashion, e.g. as done here: http://citeseer.ist.psu.edu/605753.html But with NLP you always at some point hit the wall of not having a good model of the world if you just work with grammars. - lk ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=231415&user_secret=e9e40a7e
