Granted Patent B2

US 12,651,155 · App. 17/062,753 · Granted Jun 9, 2026

Inventor: Kenneth Neumann (Lakewood, CO)

Assignee: KPN INNOVATIONS, LLC

G06N3/08G06F9/4451G06F18/214G06F18/23

Abstract

Claims (44)

1 . A system for slot linking through machine learning, the system comprising a computing device, the computing device configured to:

generate a slot profile corresponding to a slot, wherein generating the slot profile further comprises:

retrieving a plurality of elemental profiles, each elemental profile corresponding to an element of the slot; and

generating the slot profile as a function of the plurality of elemental profiles, wherein each of the plurality of elemental profiles comprises a set of quantitative values represented as an n-tuple in a multidimensional vector space, and wherein generating the slot profile comprises concatenating the plurality of elemental profiles into a data structure configured for vector comparison and normalization, wherein each of the plurality of elemental profiles is examined individually;

receive a biological extraction of an entry, wherein the biological extraction comprises physiological and psychological data obtained using a computerized questionnaire and stored in machine-readable memory;

generate an entry tendency profile associated with the entry, wherein generating the entry tendency profile further comprises:

receiving a plurality of training examples correlating biological extraction data to tendency profiles, wherein the biological extraction data comprises physiological data;

training a tendency profile model as a function of the plurality of training examples; and

generating the entry tendency profile as a function of the biological extraction and the tendency profile model;

determine an alignment quantifier as a function of the tendency profile and the slot profile, wherein determining the alignment quantifier comprises computing a proximity function between the normalized vector of the entry tendency profile and the slot profile, the proximity function comprising at least one distance metric selected from cosine similarity and Euclidean distance, and wherein the alignment quantifier comprises a quantitative value representing a degree of compatibility; and

link the entry to the slot as a function of the alignment quantifier, wherein linking the entry to the slot further comprises filtering a plurality of entries by comparing associated entry backgrounds to one or more requirements, wherein each requirement of the one or more requirements is assigned a requirement status, and wherein linking the entry to the slot further comprises automatically ranking a plurality of entries as a function of respective alignment quantifiers and filtering the plurality of entries by comparing entry background information to predefined slot requirements, each requirement being assigned a requirement status stored in memory.

2 . The system of claim 1 , wherein the elemental profiles include at least one tendency profile.

3 . The system of claim 1 , wherein the elemental profiles include at least one location profile.

4 . The system of claim 1 , wherein the elemental profiles include at least a position profile.

5 . The system of claim 1 , wherein the computing device is further configured to generate an elemental profile of the plurality of elemental profiles.

6 . The system of claim 1 , wherein generating the slot profile further comprises:

receiving slot profile training data that correlates elemental profile components with slot profile elements;

training a slot profile machine-learning model as a function of the slot profile training data; and

generating the slot profile as a function of the slot profile machine-learning model and the plurality of element profiles.

7 . The system of claim 6 , wherein the slot profile machine-learning model further comprises a neural network.

8 . The system of claim 1 , wherein the alignment quantifier is determined using a proximity function.

9 . The system of claim 1 , wherein the alignment quantifier is further determined as a function of entry background information.

10 . A method of slot linking through machine learning, the method comprising:

generating, at a computing device, a slot profile corresponding to a slot, wherein generating the slot profile further comprises:

retrieving a plurality of elemental profiles, each elemental profile corresponding to an element of the slot; and

generating the slot profile as a function of the plurality of elemental profiles, wherein each of the plurality of elemental profiles comprises a set of quantitative values represented as an n-tuple in a multidimensional vector space, and wherein generating the slot profile comprises concatenating the plurality of elemental profiles into a data structure configured for vector comparison and normalization, wherein each of the plurality of elemental profiles is examined individually;

receiving, by the computing device, a biological extraction of an entry, wherein the biological extraction comprises physiological and psychological data obtained using a computerized questionnaire and stored in machine-readable memory;

generating, by the computing device, an entry tendency profile associated with the entry, wherein generating the entry tendency profile further comprises:

receiving a plurality of training examples correlating biological extraction data to tendency profiles, wherein the biological extraction data comprises physiological data;

training a tendency profile model as a function of the plurality of training examples; and

generating the entry tendency profile as a function of the biological extraction and the tendency profile model;

determining, by the computing device, an alignment quantifier as a function of the tendency profile and the slot profile, wherein determining the alignment quantifier comprises computing a proximity function between the normalized vector of the entry tendency profile and the slot profile, the proximity function comprising at least one distance metric selected from cosine similarity and Euclidean distance, and wherein the alignment quantifier comprises a quantitative value representing a degree of compatibility; and

linking, by the computing device, the entry to the slot as a function of the alignment quantifier, wherein linking the entry to the slot further comprises filtering a plurality of entries by comparing associated entry backgrounds to one or more requirements, wherein each requirement of the one or more requirements is assigned a requirement status, and wherein linking the entry to the slot further comprises automatically ranking a plurality of entries as a function of respective alignment quantifiers and filtering the plurality of entries by comparing entry background information to predefined slot requirements, each requirement being assigned a requirement status stored in memory.

11 . The method of claim 10 , wherein the elemental profiles include at least one tendency profile.

12 . The method of claim 10 , wherein the elemental profiles include at least one location profile.

13 . The method of claim 10 , wherein the elemental profiles include at least a position profile.

14 . The method of claim 10 further comprising generating an elemental profile of the plurality of elemental profiles.

15 . The method of claim 10 , wherein generating the slot profile further comprises:

receiving slot profile training data that correlates elemental profile components with slot profile elements;

training a slot profile machine-learning model as a function of the slot profile training data; and

generating the slot profile as a function of the slot profile machine-learning model and the plurality of element profiles.

16 . The method of claim 15 , wherein the slot profile machine-learning model further comprises a neural network.

17 . The method of claim 10 , wherein the alignment quantifier is determined using a proximity function.

18 . The method of claim 10 , wherein the alignment quantifier is further determined as a function of entry background information.

Assignments (1)

Continuity (1)

References Cited (23)