1. A method comprising: automatically populating a library of query rewrite rules utilizing a Hidden Markov Model based approach; employing a first-order Hidden Markov Model to model a user's search behavior by consulting a query log; automatically learning query rewrite rules based on data in the query log; employing an augmented Hidden Markov Model to learn via obtaining click event data at each query observation via employing a click acquisition probability metric; the click acquisition probability metric representing a probability of a click occurring when observing a query, at a given time epoch, relative to a given hidden state of an underlying Markov chain; and automatically learning query rewrite rules by making use of data in the query logs and click logs.