Hi, I am not familiar with that, but somewhat related is Arne Mauser's global lexical model, which also exists as a secret feature in Moses (secret because no effiencient training exists):
Citation: A. Mauser, S. Hasan, and H. Ney. Extending Statistical Machine Translation with Discriminative and Trigger-Based Lexicon Models. In Conference on Empirical Methods in Natural Language Processing (EMNLP), Singapore, August 2009. http://www-i6.informatik.rwth-aachen.de/publications/download/628/MauserArneHasanSav%7Bs%7DaNeyHermann--ExtendingStatisticalMachineTranslationwithDiscriminativeTrigger-BasedLexiconModels--2009.pdf -phi On Fri, Oct 22, 2010 at 7:02 PM, Francis Tyers <fty...@prompsit.com> wrote: > Hello all, > > I have a rather strange request. Does anyone know of any papers (or > impementations) on bag-of-words language models ? That is, a language > model which does not take into account the order in which the words > appear in an ngram, so if you have the string 'police chief of' in your > model, you will get a result for both 'chief of police' and 'police > chief of'. I have thought of using IRSTLM or some generic model and > scoring all the permutations, but wondered if there was a more efficient > implementation already in existence. I have searched without much luck > in Google, but perhaps I am searching with the wrong words. > > Best regards, > > Fran > > _______________________________________________ > Moses-support mailing list > Moses-support@mit.edu > http://mailman.mit.edu/mailman/listinfo/moses-support > _______________________________________________ Moses-support mailing list Moses-support@mit.edu http://mailman.mit.edu/mailman/listinfo/moses-support
