The Defense Logistics Agency’s Logistics Information Services is entering the third phase of a program meant to modernize the agency’s management system that provides information about supply items used by the Department of Defense.
Launched in 2020, the Federal Logistics Information System Data Cleansing Project developed a modernized algorithmic base that uses machine learning and analytical techniques to assess multiple data sets and identify the correct data to prevent errors and inconsistencies, DLA said Monday.
During Phase III, the program will apply natural language processing techniques to transform free-text characteristics data into structured, coded replies to ensure consistency across item names.
“By harnessing the capabilities of Natural Language Processing, we gain the ability to unlock the true potential of our data—transforming unstructured information into structured insights ensuring accurate and actionable results,” said Senthil Arul, research and development program manager for the Defense Logistics Information Research, which supports the FLIS data cleansing initiative.