For each co-occurring pair of word types u and v , these likelihoods are initially set proportional to their co-occurrence frequency ( â , v ) and inversely proportional to their marginal frequencies n ( u ) and n ( v ) 1 , following ( Dunning , 1993 ) 2 .
accurate methods for the statistics of surprise and coincidencequot
T Dunning
L ( u , v ) represents the likelihood that u and v can be mutual translations . For each co-occurring pair of word types u and v , these likelihoods are initially set proportional to their co-occurrence frequency ( â , v ) and inversely proportional to their marginal frequencies n ( u ) and n ( v ) 1 , following ( Dunning , 1993 ) 2 . When the L ( u , v ) are re-estimated , the model 's hidden parameters come into play .
For each co-occurring pair of word types u and v , these likelihoods are initially set proportional to their co-occurrence frequency ( â , v ) and inversely proportional to their marginal frequencies n ( u ) and n ( v ) 1 , following ( @@CITATION ) 2 .