Apparatuses and methods for the collection and storage of user identifiers

Abstract

An apparatus for the collection and storage of user identifiers, wherein the apparatus comprises at least a processor and a memory communicatively connected to the at least a processor. The memory contains instructions configuring the at least a processor to receive user identifier data, identify a plurality of user identifier labels as a function of the user identifier data, extract a plurality of content elements from the user identifier data, classify each content element to an associated user identifier label using a content element classifier, and enter the plurality of user identifier content elements and associated user identifier labels on an immutable sequential listing.

What is claimed is: 
     
         1 . An apparatus for the collection and storage of user identifiers, the apparatus comprising:
 at least a processor; and   a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to:
 receive user identifier data, of a user, containing a plurality of content elements, wherein the plurality of content elements comprises at least a user role; 
 identify a plurality of user identifier labels, wherein identifying the plurality of user identifier labels comprises:
 training a user identifier classifier using identifier training data, wherein the identifier training data comprises user identifier data correlated to previous user identifier labels, the previous user identifier labels including previous outputs of the user classifier; 
 identifying the plurality of user identifier labels as a function of the user identifier data and the user identifier classifier, wherein the classifier is configured to receive the user identifier data as input and output at least a user identifier label; 
 
 extract, from the user identifier data, the plurality of content elements; and 
 classify each content element of the plurality of content elements to an associated user identifier label of the plurality of user identifier labels. 
   
     
     
         2 . The apparatus of  claim 1 , wherein the plurality of user identifier labels comprises a first user identifier label associated with a first professional affiliation and a second user identifier label associated with a second professional affiliation. 
     
     
         3 . The apparatus of  claim 1 , wherein receiving the user identifier data comprises receiving a user historical document comprising the user identifier data and personally identifiable information. 
     
     
         4 . The apparatus of  claim 1 , wherein receiving the user identifier data comprises receiving a user historical document, wherein the user historical document is a video document. 
     
     
         5 . The apparatus of  claim 1 , wherein extracting the plurality of content elements comprises extracting a plurality of textual elements from the user identifier data. 
     
     
         6 . The apparatus of  claim 5 , wherein classifying each content element of the plurality of content elements to the associated user identifier label of the plurality of user identifier labels comprises classifying each textual element of the plurality of textual elements to the associated user identifier label of the plurality of user identifier labels using a linguistic item classifier. 
     
     
         7 . The apparatus of  claim 6 , wherein classifying each textual element of the plurality of textual elements to the associated user identifier label of the plurality of user identifier labels using a linguistic item classifier comprises:
 training the linguistic item classifier using at least a linguistic classification training set, wherein the linguistic classification training set comprises elements of textual data and identification of objects associated with the elements of textural data; and   generating the associated user identifier label using the trained linguistic item classifier.   
     
     
         8 . The apparatus of  claim 1 , wherein the plurality of user identifier labels comprises a user identifier label for personal life and a user identifier label for work history. 
     
     
         9 . The apparatus of  claim 1 , wherein receiving the user identifier data comprises receiving at least a portion of the user identifier data from a third party validator. 
     
     
         10 . The apparatus of  claim 9 , wherein the third party validator is a friend of the user. 
     
     
         11 . A method for the collection and storage of user identifiers, wherein the method is performed by a processor and comprises:
 receiving, at the processor, user identifier data, of a user, containing a plurality of content elements, wherein the plurality of content elements comprises at least a user role;   identifying, at the processor, a plurality of user identifier labels as a function of the user identifier data, wherein identifying the plurality of user identifier labels comprises:
 training a user identifier classifier using a training dataset, wherein the training dataset comprises user identifier data correlated to previous user identifier labels, the previous user identifier labels including previous outputs of the user classifier; 
 identifying the plurality of user identifier labels as a function of the user identifier data and the user identifier classifier, wherein the classifier is configured to receive the user identifier data as input and output at least a user identifier label; 
   extracting, at the processor, from the user identifier data, the plurality of content elements; and   classifying, at the processor, each content element of the plurality of content elements to an associated user identifier label of the plurality of user identifier labels using a content element classifier.   
     
     
         12 . The method of  claim 11 , wherein the plurality of user identifier labels comprises a first user identifier label associated with a first professional affiliation and a second user identifier label associated with a second professional affiliation. 
     
     
         13 . The method of  claim 11 , wherein receiving the user identifier data comprises receiving a user historical document comprising the user identifier data and personally identifiable information. 
     
     
         14 . The method of  claim 11 , wherein receiving the user identifier data comprises receiving a user historical document, wherein the user historical document is a video document. 
     
     
         15 . The method of  claim 11 , wherein extracting the plurality of content elements comprises extracting a plurality of textual elements from the user identifier data. 
     
     
         16 . The method of  claim 15 , wherein classifying each content element of the plurality of content elements to the associated user identifier label of the plurality of user identifier labels comprises classifying each textual element of the plurality of textual elements to the associated user identifier label of the plurality of user identifier labels using a linguistic item classifier. 
     
     
         17 . The method of  claim 16 , wherein classifying each textual element of the plurality of textual elements to the associated user identifier label of the plurality of user identifier labels using a linguistic item classifier comprises:
 training the linguistic item classifier using at least a linguistic classification training set, wherein the linguistic classification training set comprises elements of textual data and identification of objects associated with the elements of textural data; and   generating the associated user identifier label using the trained linguistic item classifier.   
     
     
         18 . The method of  claim 11 , wherein the plurality of user identifier labels comprises a user identifier label for personal life and a user identifier label for work history. 
     
     
         19 . The method of  claim 11 , wherein receiving the user identifier data comprises receiving at least a portion of the user identifier data from a third party validator. 
     
     
         20 . The method of  claim 19 , wherein the third party validator is a friend of the user.