APPARATUSES AND METHODS FOR LINKING ACTION DATA TO AN IMMUTABLE SEQUENTIAL LISTING IDENTIFIER OF A USER

1 . An apparatus for linking action data to an immutable sequential listing identifier of a user, the apparatus comprising:

at least a processor; and

a memory communicatively connected to the processor, the memory containing instructions configuring the at least a processor to:

store, on an immutable sequential listing, a plurality of user identifiers, wherein:

each user identifier of the plurality of user identifiers is associated with the same user; and

each of the plurality of user identifiers is associated with a user role of the user;

receive information relating to an element of action data associated with the user, wherein the information relating to the element of action data is received from a third-party validator;

match, as a function of the received information, the action data to a particular user identifier of the plurality of user identifiers, wherein matching the action data comprises:

receiving training data including a plurality of action data entries correlated to a plurality of user identifier entries;

categorizing the training data using a classifier into a plurality of categorized training data sets;

selecting a training data set from the plurality of categorized training data sets as a function of the action data associated with the user;

training a first machine learning model using the selected training data set and a machine learning algorithm; and

matching, using the trained first machine learning model, the action data to the user identifier, wherein the action data is provided to the trained first machine learning model as an input to output the user identifier, wherein matching the action data further comprises:

validating the action data, using a second machine learning model, wherein the action data is sorted into categories of validated and non-validated action data; and

update, as a function of the matching, the user identifier stored on the immutable sequential listing, wherein updating the user identifier comprises:

updating previous action data contained in a video resume of the user by receiving updated action data;

comparing the updated action data to the action data of the third-party validator:

flagging the third-party validator if the action data and the updated action data are contradictory; and

adding a new block to the immutable sequential listing, wherein the new block comprises the updated action data.

2 . (canceled)

3 . The apparatus of claim 1 , wherein receiving information relating to the element of action data comprises mapping the element of action data to data on the immutable sequential listing.

4 . The apparatus of claim 3 , wherein receiving information relating to the element of action data further comprises classifying a plurality of mapped data to at least a user identifier.

5 . (canceled)

6 . (canceled)

7 . The apparatus of claim 1 , wherein the memory contains instructions further configuring processer to cryptographically insert into a hash chain, after validation, the element of action data of the user identifier.

8 . The apparatus of claim 1 , wherein the memory contains instructions further configuring processer to determine when the element of action data cannot be validated.

9 . The apparatus of claim 8 , wherein the memory contains instructions further configuring processer to flag the element of action data of the particular user identifier on the immutable sequential listing that could not be validated.

10 . The apparatus of claim 9 , wherein memory contains instructions further configuring processer to generate a separate record from the immutable sequential listing comprising the flagged element of action data of the particular user identifier.

11 . A method for linking action data to an immutable sequential listing identifier of a user, the method comprising:

storing, using a computing device, on an immutable sequential listing, a plurality of user identifiers, wherein:

each user identifier of the plurality of user identifiers is associated with the same user; and

each of the plurality of user identifiers is associated with a user role of the user;

receiving, using the computing device, information relating to an element of action data associated with the user, wherein the information relating to the element of action data is received from a third-party validator;

matching, using the computing device, as a function of the received information, the action data to a particular user identifier of the plurality of user identifiers, wherein matching the action data comprises:

receiving training data including a plurality of action data entries correlated to a plurality of user identifier entries;

categorizing the training data using a classifier into a plurality of categorized training data sets;

selecting a training data set from the plurality of categorized training data sets as a function of the action data associated with the user;

training a first machine learning model using the selected training data set and a machine learning algorithm; and

matching, using the trained first machine learning model, the action data to the user identifier, wherein the action data is provided to the trained first machine learning model as an input to output the user identifier, wherein matching the action data further comprises:

validating the action data, using a second machine learning model, wherein the action data is sorted into categories of validated and non-validated action data; and

updating, using the computing device, as a function of the matching, the user identifier stored on the immutable sequential listing, wherein updating the user identifier comprises:

updating previous action data contained in a video resume of the user by receiving updated action data;

comparing the updated action data to the action data of the third-party validator;

flagging the third-party validator if the action data and the updated action data are contradictory; and

adding a new block to the immutable sequential listing, wherein the new block comprises the updated action data.

12 . (canceled)

13 . The method of claim 11 , wherein receiving information relating to the element of action data comprises mapping the element of action data to data on the immutable sequential listing.

14 . The method of claim 13 , wherein receiving information relating to the element of action data further comprises classifying a plurality of mapped data to at least a user identifier.

15 . (canceled)

16 . (canceled)

17 . The method of claim 11 , wherein the memory contains instructions further configuring processer to cryptographically insert into a hash chain, after validation, the element of action data of the user identifier.

18 . The method of claim 11 , wherein the memory contains instructions further configuring processer to determine when the element of action data cannot be validated.

19 . The method of claim 18 , wherein the memory contains instructions further configuring processer to flag the element of action data of the particular user identifier on the immutable sequential listing that could not be validated.

20 . The method of claim 19 , wherein memory contains instructions further configuring processer to generate a separate record from the immutable sequential listing comprising the flagged element of action data of the particular user identifier.

21 . The apparatus of claim 1 , wherein the training data includes previous elements of matched action data of users.

22 . The apparatus of claim 21 , wherein the machine learning algorithm iteratively optimizes an objective function, wherein the objective function represents a statistical estimation of relationships between input terms and output terms.

23 . The apparatus of claim 1 , wherein the immutable sequential listing comprises a digitally signed assertion.

24 . The method of claim 11 , wherein the immutable sequential listing comprises a digitally signed assertion.