首页|Patent Application Titled 'Text Classification via Term Mapping and Machine-learning Classification Model' Published Online(USPTO 20240020474)
Patent Application Titled 'Text Classification via Term Mapping and Machine-learning Classification Model' Published Online(USPTO 20240020474)
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According to news reporting originating from Washington, D.C., by NewsRx journalists, a patent application by the inventors Akers, Peter Todd (North Potomac, MD, US); Barnes, Catherine (Glen Allen, VA, US); Honermann, Jennifer (Glen Allen, VA, US), filed on July 14, 2022, was made available online on January 18, 2024. No assignee for this patent application has been made. Reporters obtained the following quote from the background information supplied by the inventors: “Determining subject matter contained in text is tedious. While machine-based manipulations of the text may provide simplistic analyses including word frequencies and other calculatable values, collections of mere numbers fail to adequately enable one to identify the subject matter of text. Further, where the text appears across multiple documents with limited quantities of text in each document, machine-based manipulations are inadequate to summarize the content of each document or summarize the collection of documents.” In addition to obtaining background information on this patent application, NewsRx editors also ob- tained the inventors' summary information for this patent application: “The following presents a simplified summary of various aspects described herein. This summary is not an extensive overview, and is not intended to identify key or critical elements or to delineate the scope of the claims. The following sum- mary merely presents some concepts in a simplified form as an introductory prelude to the more detailed description provided below.
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