US 11,720,555 B1
Multidimensional machine learning data and user interface segment tagging engine apparatuses, methods and systems
Jason Alan Snyder, Ridgewood, NJ (US); Manuel De Araujo Pedreira Neto, New York, NY (US); Elena Klau Silverman, New York, NY (US); Stephen Michael Gorman, Hastings on Hudson, NY (US); and Michael Clark, Saint Charles, MO (US)
Assigned to Momentum NA, Inc., New York, NY (US)
Filed by Momentum NA, Inc., New York, NY (US)
Filed on Dec. 3, 2020, as Appl. No. 17/111,471.
Application 17/111,471 is a continuation in part of application No. 16/221,437, filed on Dec. 14, 2018.
Claims priority of provisional application 62/598,847, filed on Dec. 14, 2017.
Claims priority of provisional application 63/051,873, filed on Jul. 14, 2020.
Int. Cl. G06F 16/242 (2019.01); G06F 16/23 (2019.01); G06Q 30/02 (2012.01); G06Q 10/10 (2012.01); G06N 5/04 (2006.01); G06F 40/151 (2020.01); G06Q 30/0203 (2023.01)
CPC G06F 16/2433 (2019.01) [G06F 16/23 (2019.01); G06N 5/04 (2013.01); G06Q 10/10 (2013.01); G06Q 30/0203 (2013.01); G06F 40/151 (2020.01)] 18 Claims
OG exemplary drawing
 
1. A database caching engine apparatus, comprising:
a memory;
a component collection in the memory;
a processor disposed in communication with the memory and configured to issue a plurality of processor-executable instructions from the component collection, the processor-executable instructions configured to:
detect, via at least one processor, an update to a survey data file, the survey data file configured to include updated survey data comprising any of: ambient social, consumer interaction, point of sale, third party, internet of things, and internal survey data;
store, via at least one processor, the updated survey data in a SQL database, the SQL database configured to utilize a composite index of the updated survey data that optimizes database query time;
determine, via at least one processor, a set of affected entity segment identifiers, the set of affected entity segment identifiers configured to include a respective entity segment identifier upon determining that the updated survey data includes a respondent identifier associated with the respective entity segment identifier, an entity segment identifier configured to identify an entity comprising any of: person, item of manufacture, service, asset, brand, ad, category of manufacture, category of service, category of person, demographic, sentiment;
determine, via at least one processor, a set of affected category identifiers, the set of affected category identifiers configured to include a respective category identifier upon determining that the updated survey data includes an allowable response question identifier associated with the respective category identifier;
determine, via at least one processor, a set of affected cognitive intelligence (CI) datapoint identifiers, the set of affected CI datapoint identifiers configured to include CI datapoint identifiers associated with each combination of: an affected entity segment identifier and an affected category identifier;
instantiate, via at least one processor, a set of cache datastructures, the set of cache datastructures configured to include a cache datastructure for each affected CI datapoint identifier, a cache datastructure configured as a key-value pair comprising an associated affected CI datapoint identifier and a CI datapoint value corresponding to the associated affected CI datapoint identifier;
calculate, via at least one processor, a set of metrics for each allowable response question identifier associated with each affected CI datapoint identifier using the updated survey data; and
store, via a cache datastructure via at least one processor, the calculated metrics for each affected CI datapoint identifier in a NoSQL database, the NoSQL database configured to act as cache for generating visualizations.