On 11/28/07, Grzegorz Chrupala
You may have better luck checking out methods used in parsing natural language. In order to use statistical parsing techniques such as Probabilistic Context Free Grammars ([1],[2] ) the standard approach is to extract rule probabilities from an annotated corpus, that is collection of strings with associated parse trees. Maybe you could use your 2/3 of addresses that you know are correctly parsed as your training material.
A PCFG parser can output all (or n-best) parses ordered according to probabilities so that would seem to be fit your requirements. [1] http://en.wikipedia.org/wiki/Stochastic_context-free_grammar [2] http://www.cs.colorado.edu/~martin/slp2.html#Chapter14 -- Best, Grzegorz --
Hi Grzegorz, Wow, Natural Language Processing looks quite complex! But it also seems to be closely related to my problem. If someone finds a "NPL for dummies" article or book I'm interested. ;-) Thanks for your help, Olivier.