Text embedding analysis tool
Description
Reviewing large sets of documents can take hours to identify similar clusters or analysis. The tool helps non-technical staff explore large, text-based datasets by generating clusters of text and identifying similar documents.
Detailed example
The system generates text embeddings and then understand how their documents cluster in the embedding space. The system has no default output--it's primarily an AI-enabled canvas for drawing the embedding space and helping users explore the space rigorously. Users may, however, choose to export the embeddings, cluster assignments, or modified source datasets for use in other downstream analyses.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
One benefit is being able to get a quick-but-principled analytic overview of a (potentially very large) text corpus's semantic content. This may yield time savings for tasks like responding to public inquiries and doing qualitative analyses of unstructured datasets.
Controls / human review
ATO: Yes; PIA: Not published