The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Mar. 26, 2024
Filed:
May. 19, 2022
International Business Machines Corporation, Armonk, NY (US);
Raghu Kiran Ganti, White Plains, NY (US);
Mudhakar Srivatsa, White Plains, NY (US);
Shreeranjani Srirangamsridharan, San Jose, CA (US);
Jae-Wook Ahn, Nanuet, NY (US);
Michele Merler, New York City, NY (US);
Dean Steuer, White Plains, NY (US);
International Business Machines Corporation, Armonk, NY (US);
Abstract
Systems, methods and/or computer program products for controlling and visualizing topic modeling results using a topic modeling interface. The interface allows user directed exploration, understanding and control of topic modeling algorithms, while offering both semantic summaries and/or structure attribute explanations about results. Explanations and differentiations between results are presented using metrics such as cohesiveness and visual displays depicting hierarchical organization. Through user-manipulation of features of the interface, iterative changes are implemented through user-feedback, adjusting parameters, broadening or narrowing topic results, and/or reorganizing topics by splitting or merging topics. As users trigger visual changes to results being displayed, users can compare and contrast output from the topic modeling algorithm. With each change to parameters, users view different explanations informing the user why the changes being displayed occurred, providing users deeper understanding of the topic modeling process, how to manipulate parameters to achieve accurate topic results and adjust granularity of information presented.