Generally, given a non-smoothed document language model P (w|d), which indicates a word distribution for a term w in document d, we attempt to generate a smoothed language model P (w|d + ) that could better estimate the text contents of a document d as d + to avoid zero probabilities for those words not seen in d. Arbitrary assignment of pseudo word counts such as add-λ to every unseen words once was a major improvement for language model smoothing (Chen and Goodman, 1996).
the purpose of smoothing is to estimate language model more accurately.