Southern Methodist University

Personalweb Technologies, LLC

Jake Drew

Joshua Cade Jarvis

Bobby Charles Thomas

Tyler Moore

Michael Hahsler

Wasef Kassis

William Robert Zink

The present invention relates in general to the field of parallel data processing, and more particularly to machine learning and classification of extremely large volumes of unstructured gene sequence data using Collaborative Analytics Gene Sequence Classification Learning Systems and Methods.

System and method for machine learning and classifying data

A computer-implemented method, implemented, at least in part, by hardware in combination with software, the method includes (A) obtaining text from a document; (B) parsing said text using at least one parallel sentence parsing process to obtain sentence data from said text; (C) parsing said sentence data using at least one parallel noun parsing process to obtain text data from said sentence data; (D) scoring said text data using at least one term scorer process and a known word list to obtain scored terms corresponding to said text data; and (E) determining known word scores corresponding to said text data, using said known word list, wherein said known word scores comprise base scores and category penetration scores; wherein steps (B), (C), (D), and (E) operate in parallel for at least some of the text from the document.

Universal language classification devices, systems, and methods

Growing community of inventors

Canton, TX, United States of America

Jake Drew