Unfortunately, in retrieval, we often have to estimate a model based on a small sample of data (e.g., a single document or only a few documents).
given limited data sampling, a language model estimation sometimes encounters with the zero count problem: the maximum likelihood estimator would give unseen terms a zero probability, which is not reliable because a larger sample of the data would likely contain the term.