US 11,698,919 B2
Aggregating data to form generalized profiles based on archived event data and compatible distributed data files with which to integrate data across multiple data streams
Adam Eric Katz, New York, NY (US); Aman Raghuvanshi, Monmouth Junction, NJ (US); Adam Jarrell Smith, San Diego, CA (US); and Jacob Maximillian Miesner, New York, NY (US)
Assigned to Sightly Enterprises, Inc., San Diego, CA (US)
Filed by Sightly Enterprises, Inc., San Diego, CA (US)
Filed on May 7, 2021, as Appl. No. 17/314,646.
Prior Publication US 2022/0358147 A1, Nov. 10, 2022
Int. Cl. G06F 16/00 (2019.01); G06F 16/28 (2019.01); G06F 9/54 (2006.01)
CPC G06F 16/285 (2019.01) [G06F 9/544 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method comprising:
receiving different data streams via a message throughput data pipe associated with multiple data sources each associated with a processor and memory, the data including at least a portion of executable instructions;
extracting a plurality of features from one or portions of data or the executable instructions to form a plurality of extracted features;
characterizing the plurality of features to classify portions of data as types of one or more of text, video, and audio;
aggregating data representing the plurality of features to form one or more brand intelligence profiles defining the multiple data sources;
receiving integration data to integrate with the subset of the multiple data sources;
filtering the integration data against data representing the one or more brand intelligence profiles to identify the subset of the multiple data sources;
activating a subset of application programming interfaces to transmit a subset of integration data to integrate with the subset of the multiple data sources;
correlating the plurality of extracted features as event data across the different data streams;
computing a rate of diffusivity of the event data; and
identifying data files at the subset of the multiple data sources based on the rate of diffusivity.