We formulate answer selection as a semantic matching problem with a latent word-alignment structure as in (Chang et al., 2010) and conduct a series of experimental studies on leveraging recently proposed lexical semantic models.
a recurrent neural network language model (Mikolov et al., 2010) aims to estimate the probability of observing a word given its preceding context.