US 11,874,843 B1
Apparatus and methods for tracking progression of measured phenomena
Barbara Sue Smith, Toronto (CA); and Daniel J. Sullivan, Toronto (CA)
Assigned to Strategic Coach, Toronto (CA)
Filed by Strategic Coach, Toronto (CA)
Filed on May 1, 2023, as Appl. No. 18/141,827.
Int. Cl. G06F 16/20 (2019.01); G06F 16/2457 (2019.01); G06F 3/0482 (2013.01)
CPC G06F 16/24575 (2019.01) [G06F 3/0482 (2013.01); G06F 16/24578 (2019.01)] 24 Claims
OG exemplary drawing
 
1. An apparatus for tracking progress of measured phenomena, the apparatus comprising:
at least a processor;
a memory communicatively connected to the processor, the memory containing instructions configuring the at least a processor to:
receive a user datum;
generate an interface query data structure including at least a query including an input field based on the user datum, wherein the interface query data structure configures a remote display device to:
display the input field to the user;
receive at least a first user-input datum into the input field;
retrieve data describing attributes of the user from a database communicatively connected with the processor; and
refine the interface query data structure based on data describing attributes of the user from the database;
generate multiple data multipliers based on the first user-input datum, wherein:
each data multiplier includes multiple data values including relatively higher data values describing data indicative of progress of the user toward matching a target; and
at least some data multipliers are generated and scored using a machine learning model including a classifier configured to correlate the user datum and the first user-input datum to data describing the target into an ordered list based on score;
generate a strategy data for the user based on the first user-input datum, relatively higher data values, and the ordered list, wherein:
the strategy data is generated in response to a data multiplier instruction defined as multiplying at least the first user-input datum by relatively higher data values and displaying feedback to the user according to the ordered list; and
the interface query data structure configures the remote display device to:
display at least the strategy data;
receive a second user-input datum through the remote display device corresponding to at least some aspects of the strategy data, the second user-input datum demonstrating either a similarity or a dissimilarity to the first user-input datum, the strategy data configured to be iteratively recalculated based on the second user-input datum by at least the machine learning model; and
display the performance data output to the user.