In natural language processing, a classic example of a sparse feature is the occurrence of a rare word within a text corpus. For instance, the word 'preconditioning' appears much less frequently than a common word like 'learning'. Consequently, the parameter or feature associated with 'preconditioning' is mostly inactive and only receives meaningful updates on the rare occasions it is actually observed. This characteristic of infrequent occurrence is also prevalent in other practical domains, such as computational advertising and personalized collaborative filtering, where specific items are typically of interest to only a small subset of users.