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.

Date of Patent:
Sep. 20, 2016

Filed:

Oct. 24, 2014
Applicant:

Blab, Inc., Seattle, WA (US);

Inventors:

Randolph Browning, Mercer Island, WA (US);

Stefan Nicholas Papp, Seattle, WA (US);

Bernhard G. Zimmermann, Seattle, WA (US);

Benjamin Ralph Bressler, Sammamish, WA (US);

Assignee:

Blab, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 12/18 (2006.01); H04L 29/08 (2006.01); H04L 12/26 (2006.01); G06F 17/27 (2006.01); G06Q 50/00 (2012.01); G06Q 10/10 (2012.01); G06N 5/02 (2006.01); G06Q 30/02 (2012.01); G06N 5/04 (2006.01);
U.S. Cl.
CPC ...
H04L 12/1831 (2013.01); H04L 43/045 (2013.01); H04L 67/18 (2013.01); H04L 67/22 (2013.01); G06F 17/2785 (2013.01); G06N 5/02 (2013.01); G06N 5/046 (2013.01); G06Q 10/10 (2013.01); G06Q 30/02 (2013.01); G06Q 50/01 (2013.01);
Abstract

Techniques are described for analyzing user-supplied information and/or predicting future aspects of additional information that will be supplied by users. The analyzed information may include distributed group discussions involving numerous users, occurring via user comments and other content items supplied to social networking site(s) and/or other sources. Analysis of user-supplied information may, for example, include determining particular topics and/or categories of interest during one or more time periods and quantifying corresponding amounts of user interest; determining trends for, relevant terms and attributes for, and inter-relationships between the topics and categories; predicting future amounts of user interest in the topics and categories; tracking user interactions with information about the topics and/or categories; and taking further actions based on the analyzed and/or predicted information.


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