JM smoothing uses a fixed parameter λ to control the interpolation: while the Dirichlet smoothing uses a documentdependent coefficient (parameterized with µ) to control the interpolation: Here P (w|Θ C ) is the probability of word w given by the collection language model Θ C , which is usually estimated using the whole collection of documents C, e.g., P (w|Θ C ) = Recently, the cluster structure of the corpus has been exploited to improve language models for retrieval (Kurland and Lee, 2004;Liu and Croft, 2004).
the cluster-based language model proposed in (Liu and Croft, 2004) uses clustering information to further smooth a document model.