Multidimensional machine learning data and user interface segment tagging engine apparatuses, methods and systems
The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A category identifier selection is obtained via a category selection interaction interface mechanism. Entity segment identifier selections are obtained via entity segment selection interaction interface mechanisms. A set of visualization cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of a selected entity segment identifier and the selected category identifier. CI datapoint values corresponding to the set of visualization CI datapoint identifiers are retrieved from a NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data. A visualization is generated using the retrieved CI datapoint values.
1. A cognitive intelligence visualization 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:
obtain, via at least one processor, a category identifier selection via a category selection interaction interface mechanism;
obtain, via at least one processor, a first entity segment identifier selection via a first entity segment selection interaction interface mechanism;
obtain, via at least one processor, a second entity segment identifier selection via a second entity segment selection interaction interface mechanism;
determine, via at least one processor, a set of visualization cognitive intelligence (CI) datapoint identifiers, the set of visualization CI datapoint identifiers configured to include CI datapoint identifiers associated with each combination of: a selected entity segment identifier and the selected category identifier;
retrieve, via at least one processor, for each CI datapoint identifier in the set of visualization CI datapoint identifiers, a CI datapoint value corresponding to the respective CI datapoint identifier from a NoSQL database via a cache datastructure, the NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data, a cache datastructure configured as a key-value pair comprising an associated CI datapoint identifier and a CI datapoint value corresponding to the associated CI datapoint identifier;
generate, via a cache datastructure via at least one processor, a visualization using the retrieved CI datapoint values, the visualization configured to display a set of metrics, for a set of utilized allowable response question identifiers associated with the selected category identifier, for each selected entity segment identifier.
2. The apparatus of claim 1 , further, comprising:
a category identifier is configured to identify a user interface section.
3. The apparatus of claim 1 , further, comprising:
an entity segment identifier is 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.
4. The apparatus of claim 1 , further, comprising:
the processor-executable instructions configured to:
obtain, via at least one processor, a third entity segment identifier selection via a third entity segment selection interaction interface mechanism.
5. The apparatus of claim 1 , further, comprising:
a CI datapoint identifier is configured to comprise an entity segment identifier and a category identifier.
6. The apparatus of claim 5 , further, comprising:
a CI datapoint value is configured as a datastructure comprising a set of module datastructures, each module datastructure corresponding to a module identifier associated with the category identifier specified as part of the associated CI datapoint identifier, each module datastructure comprising a set of metric datastructures, each metric datastructure corresponding to a set of calculated metrics, for an allowable response question identifier associated with the respective module datastructure's module identifier, for an entity segment identifier specified as part of the associated CI datapoint identifier.
7. The apparatus of claim 6 , further, comprising:
a CI datapoint value is configured to be stored in the NoSQL database in JSON format.
8. The apparatus of claim 1 , further, comprising:
the survey data is configured to comprise any of: ambient social, consumer interaction, point of sale, third party, internet of things, and internal survey data.
9. The apparatus of claim 1 , further, comprising:
the processor-executable instructions configured to:
determine, via at least one processor, a set of module identifiers associated with the selected category identifier;
obtain, via at least one processor, a module identifier selection via a module selection interaction interface mechanism, the module selection interaction interface mechanism configured to facilitate selection of a module identifier from the set of module identifiers associated with the selected category identifier; and
determine, via at least one processor, the set of utilized allowable response question identifiers as a set of allowable response question identifiers associated with the selected module identifier.
10. The apparatus of claim 9 , further, comprising:
the processor-executable instructions configured to:
obtain, via at least one processor, a second module identifier selection via the module selection interaction interface mechanism;
determine, via at least one processor, a second set of utilized allowable response question identifiers as a set of allowable response question identifiers associated with the selected second module identifier; and
generate, via a cache datastructure via at least one processor, a second visualization using the retrieved CI datapoint values, the second visualization configured to display a second set of metrics, for the second set of utilized allowable response question identifiers associated with the selected category identifier, for each selected entity segment identifier.
11. A cognitive intelligence visualization engine processor-readable, non-transient medium, comprising processor-executable instructions configured to:
obtain, via at least one processor, a category identifier selection via a category selection interaction interface mechanism;
obtain, via at least one processor, a first entity segment identifier selection via a first entity segment selection interaction interface mechanism;
obtain, via at least one processor, a second entity segment identifier selection via a second entity segment selection interaction interface mechanism;
determine, via at least one processor, a set of visualization cognitive intelligence (CI) datapoint identifiers, the set of visualization CI datapoint identifiers configured to include CI datapoint identifiers associated with each combination of: a selected entity segment identifier and the selected category identifier;
retrieve, via at least one processor, for each CI datapoint identifier in the set of visualization CI datapoint identifiers, a CI datapoint value corresponding to the respective CI datapoint identifier from a NoSQL database via a cache datastructure, the NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data, a cache datastructure configured as a key-value pair comprising an associated CI datapoint identifier and a CI datapoint value corresponding to the associated CI datapoint identifier;
generate, via a cache datastructure via at least one processor, a visualization using the retrieved CI datapoint values, the visualization configured to display a set of metrics, for a set of utilized allowable response question identifiers associated with the selected category identifier, for each selected entity segment identifier.
12. A cognitive intelligence visualization engine processor-implemented system, comprising:
means to process processor-executable instructions;
means to issue processor-issuable instructions from a processor-executable component collection via the means to process processor-executable instructions, the processor-issuable instructions configured to:
obtain, via at least one processor, a category identifier selection via a category selection interaction interface mechanism;
obtain, via at least one processor, a first entity segment identifier selection via a first entity segment selection interaction interface mechanism;
obtain, via at least one processor, a second entity segment identifier selection via a second entity segment selection interaction interface mechanism;
determine, via at least one processor, a set of visualization cognitive intelligence (CI) datapoint identifiers, the set of visualization CI datapoint identifiers configured to include CI datapoint identifiers associated with each combination of: a selected entity segment identifier and the selected category identifier;
retrieve, via at least one processor, for each CI datapoint identifier in the set of visualization CI datapoint identifiers, a CI datapoint value corresponding to the respective CI datapoint identifier from a NoSQL database via a cache datastructure, the NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data, a cache datastructure configured as a key-value pair comprising an associated CI datapoint identifier and a CI datapoint value corresponding to the associated CI datapoint identifier;
generate, via a cache datastructure via at least one processor, a visualization using the retrieved CI datapoint values, the visualization configured to display a set of metrics, for a set of utilized allowable response question identifiers associated with the selected category identifier, for each selected entity segment identifier.
13. A cognitive intelligence visualization engine processor-implemented process, comprising executing processor-executable instructions to:
obtain, via at least one processor, a category identifier selection via a category selection interaction interface mechanism;
obtain, via at least one processor, a first entity segment identifier selection via a first entity segment selection interaction interface mechanism;
obtain, via at least one processor, a second entity segment identifier selection via a second entity segment selection interaction interface mechanism;
determine, via at least one processor, a set of visualization cognitive intelligence (CI) datapoint identifiers, the set of visualization CI datapoint identifiers configured to include CI datapoint identifiers associated with each combination of: a selected entity segment identifier and the selected category identifier;
retrieve, via at least one processor, for each CI datapoint identifier in the set of visualization CI datapoint identifiers, a CI datapoint value corresponding to the respective CI datapoint identifier from a NoSQL database via a cache datastructure, the NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data, a cache datastructure configured as a key-value pair comprising an associated CI datapoint identifier and a CI datapoint value corresponding to the associated CI datapoint identifier;
generate, via a cache datastructure via at least one processor, a visualization using the retrieved CI datapoint values, the visualization configured to display a set of metrics, for a set of utilized allowable response question identifiers associated with the selected category identifier, for each selected entity segment identifier.