SBIR Phase I: Automatic Editing Through Semantic Alignment with Deep Learning

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 1721878
Agency Tracking Number: 1721878
Amount: $225,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: IT
Solicitation Number: N/A
Timeline
Solicitation Year: 2016
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-07-01
Award End Date (Contract End Date): 2018-06-30
Small Business Information
1537 N. Ivanhoe St, Arlington, VA, 22205-2742
DUNS: 080249859
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jonathan Herr
 (202) 731-8905
 jonathanherr@gmail.com
Business Contact
 Jonathan Herr
Phone: (202) 731-8905
Email: jonathanherr@gmail.com
Research Institution
N/A
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to render the tedious, time-consuming, and expensive manual process of contract review and negotiation as archaic. The outcome from the proposed research will accurately review and negotiate in-bound contracts based on a user's history of reviewing and negotiating just a handful of similar contracts and will result in (a) a 50-90% reduction in companies' contract review and negotiation time and (b) standardized risk across all contracts within an organization. Furthermore, the proposed research will provide small and medium-sized businesses with the ability to afford and obtain the same quality of legal review of in-bound contracts as the largest and most sophisticated companies in the world. This Small Business Innovation Research Phase I Project will develop the first system to automate edits in contracts through semantic sentence alignment with deep learning techniques. The proposed research will expand upon state-of-the-art methodologies for unsupervised learning of distributed representation of various length text segments and then launch the first and only machine learning platform that automates contract review and negotiation with semantic editing capabilities.

* Information listed above is at the time of submission. *

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