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ENT:Extended Nestor Tagging

Award Information
Agency: Department of Commerce
Branch: National Institute of Standards and Technology
Contract: 70NANB20H122
Agency Tracking Number: 048-FY20-73
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 9.0
Solicitation Number: 2020-NIST-SBIR-01
Solicitation Year: 2020
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-09-01
Award End Date (Contract End Date): 2021-02-28
Small Business Information
5520 Research Park Drive, Baltimore, MD, 21228
DUNS: 793932310
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: Y
Principal Investigator
 Maryam Esmaeilkhanian
 (443) 543-5476
Business Contact
 Maryam Esmaeilkhanian
Phone: (443) 543-5476
Research Institution
In order for manufacturers to adopt data-driven decision making, they must tap into unstructured data that sits unused. The process of annotation and knowledge extraction from unstructured text data is a time consuming and challenging bottleneck to adopting machine learning at scale.  This Phase I SBIR proposes implementation of an enhanced cloud-based platform enabling maintenance and other organizational users to tag and extract knowledge from large volumes of unstructured text data more efficiently. In Nestor, NIST provides an NLP toolkit that assigns tags and rules to unstructured data by a ranked tagging procedure. Combining this approach with RedShred’s state of the art enrichment platform will accelerate an organization’s ability to rapidly develop and deploy these models to support evolving organizational needs. The extended system, ENT, will include customizable ranking allowing organizations to tailor which data are prioritized based on business value as well as interactive UI dashboards providing real-time feedback. This combined system provides a valuable low-friction solution to accelerate adoption of NLP technologies in manufacturing to unlock value from previously idle log data repositories.

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

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