Budget Area Topic Classification Tool
Description
The Budget Area Topic Classification Tool uses a pre-trained Bidirectional Encoder Representations from Transformers (BERT) model ('bert-base-uncased') to classify proposals into 1 of 8 budget areas: Advanced Manufacturing, Artificial Intelligence, Advanced Wireless, Clean Energy, Microelectronics & Semiconductors, Quantum, or Trustworthy AI. This approach is semi-supervised in nature as the training data is comprised of pre-tagged Computer and Information Science and Engineering (CISE) proposals from prior years. Upon training the model to learn the multi-label structure of the underlying data, the model's accuracy and discriminatory power was tested using a hold-out sample (i.e., 80/20 split). The model outputs a numerical vector of probabilities representing the likelihood that a given proposal belongs to 1 or more categories. A cut-off value can then be set for determining the final classification for a given proposal.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Controls / human review
ATO: Not reported; PIA: Not published