An official website of the United States government
Here’s how you know
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Sarala Padi, Spencer J. Breiner, Eswaran Subrahmanian, Ram D. Sriram
In this paper we analyze elements of the Unified Modeling Language (UML), specifically the class diagram, and propose an simplified alternative language based
Spencer J. Breiner, Blake S. Pollard, Eswaran Subrahmanian
This report presents the summary of a workshop held at NIST on March 15-16, 2018 on the topic of applied category theory (ACT). The meeting had two main goals:
Dhananjay Anand, Blake S. Pollard, Spencer J. Breiner, John S. Nolan, Eswaran Subrahmanian
The problem of integrating multiple overlapping models and data is pervasive in engineering, though often implicit. We consider this issue of model management
Spencer J. Breiner, Ram D. Sriram, Eswaran Subrahmanian
In this chapter we argue for the use of representations from category theory to support better models for complex systems, and provide an example of such an
Talapady N. Bhat, John T. Elliott, Ursula R. Kattner, Carelyn E. Campbell, Eswaran Subrahmanian, Ram D. Sriram, Jacob Collard, Monarch Ira
Motivated by the need for exible, intuitive, reusable, and normalized ter- minology for the semantic web, we present a general approach for generat- ing sets of
John T. Elliott
,
Talapady N. Bhat
,
Ursula R. Kattner
,
Carelyn E. Campbell
,
Ram D. Sriram
,
Eswaran Subrahmanian
and
Jacob Collard
Patent Description This method is a general approach to generating sets of normalized terminology from a digital corpus of natural language documents in any given domain to address the need for flexible, intuitive, reusable, and normalized terminology. The terms that this approach generates are root