US 12,260,307 B2
Apparatus and a method for digital asset map generation
David Imrem, Bloomington, IN (US); and Reuben Vandeventer, Bloomington, IN (US)
Assigned to Duo Dimensio, LLC, Bloomington, IN (US)
Filed by Duo Dimensio, LLC, Bloomington, IN (US)
Filed on Apr. 3, 2023, as Appl. No. 18/130,257.
Prior Publication US 2024/0330744 A1, Oct. 3, 2024
Int. Cl. G06N 20/00 (2019.01)
CPC G06N 20/00 (2019.01) 16 Claims
OG exemplary drawing
 
1. An apparatus for digital assets map generation, the apparatus comprises:
a digital environment communicatively connecting a plurality of digital devices, wherein the digital environment comprises a firewall inserted in between a plurality of data connections between the plurality of digital devices wherein the firewall is configured to control access rules of the digital environment;
at least one processor operating in the digital environment; and
a memory communicatively connected to the at least one processor, wherein the memory contains instructions configuring the at least one processor to:
receive a digital collection from an entity;
identify a plurality of digital assets from the digital collection;
traverse the plurality of digital assets identified from the digital collection, wherein traversing further comprises identifying at least a data path connecting the plurality of digital assets;
determine at least one unique object within the plurality of digital assets as a function of the traversal;
train a digital asset map machine learning model, wherein training a digital asset map machine learning model comprises:
applying digital asset training data to an input layer of nodes comprising an input layer of nodes comprising a plurality of digital assert set inputs, an intermediate layer of nodes, and at least an output layer of nodes comprising a plurality of digital assert map outputs;
adjusting one or more connections and one or more weights between nodes in adjacent layers of the digital asset map machine learning model;
detecting additional correlations between the output layer of nodes and the input layer of nodes;
retraining the digital asset map machine learning model as a function of the additional correlations; and
generate a digital asset map as a function of the trained digital asset map machine learning model and the at least one unique object, wherein the digital asset map comprises:
a plurality of nodes further comprising:
root nodes;
intermediate nodes; and
terminal nodes;
a plurality of edges connected between all the root nodes, terminal nodes, and intermediate nodes, wherein an edge of the plurality of edges comprises a ring edge with a direction that points back towards a terminal node; and
a plurality of digital assets paths, wherein each digital asset path comprises:
a complete path from root nodes to terminal nodes; and
nodes traversal based on the plurality of edges connected in between the nodes; and
display the generated digital asset map using a visual interface, wherein each node of the plurality of nodes comprises an interaction component configured to access a user operation datum and the at least one unique object linked to the user operation datum.