  In this paper, we unveil a groundbreaking method to amplify full-text search
lemmatization, utilizing the OpenCorpora dataset and a bespoke paradigm
retrieval algorithm. Our primary aim is to streamline the extraction of a
word's primary form or lemma - a crucial factor in full-text search.
Additionally, we propose a compact dictionary storage strategy, significantly
boosting the speed and precision of lemma retrieval.
