Enabling FOIA Request Clustering Capability in the Document Review Platform (Density Based Algorithm alongside Term Frequency – Inverse Document Frequency (TF-IDF))
Description
Identifying Contextually Similar FOIA Requests. Developed in house is selected because while the document review platform is used it is not an out of the box functionality.
Detailed example
Grouped requests into clusters based on TF-IDF weighted vocabulary. Documents with distinctive overlapping terms form conceptual groups. This provides a visualization of requests that are conceptually similar. The clusters assist in identifying emerging topics of public interest, opportunities where proactive disclosure may fulfill multiple requests, and opportunities for collaboration on responses across multiple bureaus. While we primarily use our own in-house built tool for this capability, there are times when we still leverage this version.
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
This tool assists in identifying contextually similar FOIA requests but has some limitations such as editing stop words. While we still use this tool sometimes, we primarily use our in-house built tool.
Controls / human review
ATO: No; PIA: Not published
Data needed
FOIA requests