NLP-based Portfolio Analysis
Creating a more efficient grant portfolio analysis process through natural language programming
Executive Summary
With grant portfolios changing every year and ranging from 10 to 100 projects, program officers and analysts spend a lot of their time manually scanning the text of grants on QVR to track the specific details of their funded projects. We propose creating a tool that uses natural language programing (NLP) to search through a grant application for defined text to answer program officer’s questions. This will increase the speed of analyzing portfolios and improve the overall management of grant portfolios.
Team Members
Bishen Singh (Team Lead), NIH/NIMH
Michael Addis, NIH/NIMH
Milestones
January 2017: Project selected into the HHS Ignite Accelerator
January 2017: Time in Accelerator Began
May 2017: Time in Accelerator Ended
