US-12619297-B2 - Methods and systems for using artificial intelligence to analyze user activity data

Abstract

A system for using artificial intelligence to analyze user activity data, the system comprising a computing device configured to receive from a user, at least a biological extraction and at least a user activity datum, determine a current user location, generate a diagnostic output as a function of the biological extraction, wherein the diagnostic output comprises a condition of the user, retrieve, from a fingerprint database, at least a datum of user fingerprint data, identify a plurality of compatible elements at the current user location as a function of the condition of the user, select at least a compatible element as a function of the fingerprint data, and present, via a graphical user interface, the at least a compatible element to a user device.

Inventors

• Kenneth Neumann

Assignees

• KPN INNOVATIONS, LLC.

Dates

Publication Date

20260505

Application Date

20230821

Claims (20)

1. 1 . A system for using artificial intelligence to analyze user activity data, the system comprising: a computing device, wherein the computing device is designed and configured to: receive from a user, at least a biological extraction and user fingerprint data; identify at least one filter criteria based on the at least a biological extraction and the at least a datum of user fingerprint data; identify a plurality of compatible elements; select at least a compatible element from the plurality of compatible elements as a function of the at least a datum of user fingerprint data, wherein selecting the at least a compatible element comprises: filtering the plurality of compatible elements using the at least one filter criteria; and selecting the at least a compatible element from the filtered plurality of compatible elements; and present, using a graphical user interface, the at least a compatible element to a user device.
2. 2 . The system of claim 1 , wherein the at least a biological extraction comprises physiological state data.
3. 3 . The system of claim 1 , wherein the user fingerprint data comprises information describing at least an action performed by the user in relation to a search query during a search session.
4. 4 . The system of claim 1 , wherein the user fingerprint data comprises data describing user's spending behaviors.
5. 5 . The system of claim 4 , wherein the user's spending behaviors comprises compatible element ordering behaviors.
6. 6 . The system of claim 1 , wherein the user fingerprint data comprises: a plurality of user fingerprint datums, wherein each user fingerprint datum comprises at least a correlated compatibility label.
7. 7 . The system of claim 6 , wherein identifying the at least one filter criteria comprise: generating an overall significance score for each the at least a correlated compatibility label of each user fingerprint datum; and ranking the plurality of user fingerprint datums based on the overall significance scores.
8. 8 . The system of claim 6 , wherein identifying the at least one filter criteria comprise: classifying the at least a correlated compatibility label into a brand inquiry; and identify the at least one filter criteria as a function of the brand inquiry.
9. 9 . The system of claim 1 , wherein filtering the plurality of compatible elements comprises: removing one or more compatible elements according to the at least one filter criteria.
10. 10 . The system of claim 1 , wherein identifying the plurality of compatible elements further comprises: generating, using a ranking machine-learning process, a plurality of compatibility metrics for a plurality of alternative compatible elements, wherein each compatibility metric quantifies a compatible element ordering behavior for each compatible element as a function of a user condition; and ranking the plurality of compatible elements as a function of the plurality of compatibility metrics.
11. 11 . A method for using artificial intelligence to analyze user activity data, the method including: receiving from a user, by a computing device, at least a biological extraction and user fingerprint data; identifying, by the computing device, at least one filter criteria based on the at least a biological extraction and the at least a datum of user fingerprint data; identifying, by the computing device, a plurality of compatible elements; selecting, by the computing device, at least a compatible element from the plurality of compatible elements as a function of the at least a datum of user fingerprint data, wherein selecting the at least a compatible element comprises: filtering the plurality of compatible elements using the at least one filter criteria; and selecting the at least a compatible element from the filtered plurality of compatible elements; and presenting by the computing device, using a graphical user interface, the at least a compatible element to a user device.
12. 12 . The method of claim 11 , wherein the at least a biological extraction comprises physiological state data.
13. 13 . The method of claim 11 , wherein the user fingerprint data comprises information describing at least an action performed by the user in relation to a search query during a search session.
14. 14 . The method of claim 11 , wherein the user fingerprint data comprises data describing user's spending behaviors.
15. 15 . The method of claim 14 , wherein the user's spending behaviors comprises compatible element ordering behaviors.
16. 16 . The method of claim 11 , wherein the user fingerprint data comprises: a plurality of user fingerprint datums, wherein each user fingerprint datum comprises at least a correlated compatibility label.
17. 17 . The method of claim 16 , wherein identifying the at least one filter criteria comprise: generating an overall significance score for each the at least a correlated compatibility label of each user fingerprint datum; and ranking the plurality of user fingerprint datums based on the overall significance scores.
18. 18 . The method of claim 16 , wherein identifying the at least one filter criteria comprise: classifying the at least a correlated compatibility label into a brand inquiry; and identify the at least one filter criteria as a function of the brand inquiry.
19. 19 . The method of claim 11 , wherein filtering the plurality of compatible elements comprises: removing one or more compatible elements according to the at least one filter criteria.
20. 20 . The method of claim 11 , wherein identifying the plurality of compatible elements further comprises: generating, using a ranking machine-learning process, a plurality of compatibility metrics for a plurality of alternative compatible elements, wherein each compatibility metric quantifies a compatible element ordering behavior for each compatible element as a function of a user condition; and ranking the plurality of compatible elements as a function of the plurality of compatibility metrics.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application is a continuation of Non-provisional application Ser. No. 17/884,710 filed on Aug. 10, 2022 and entitled “METHODS AND SYSTEM FOR USING ARTIFICIAL INTELLIGENCE TO ANALYZE USER ACTIVITY DATA,” which is a continuation of Non-provisional application Ser. No. 17/087,727 filed on Nov. 3, 2020 and entitled “METHODS AND SYSTEMS FOR USING ARTIFICIAL INTELLIGENCE TO ANALYZE USER ACTIVITY DATA,” which is a continuation-in-part of Non-provisional application Ser. No. 16/532,283 filed on Aug. 5, 2019 and entitled “METHODS AND SYSTEMS FOR USING ARTIFICIAL INTELLIGENCE TO ANALYZE USER ACTIVITY DATA,” each of which are incorporated herein by reference in their entirety. FIELD OF THE INVENTION The present invention generally relates to the field of machine-learning. In particular, the present invention is directed to methods and systems for using artificial intelligence to analyze user activity data. BACKGROUND Accurate selection of compatible elements as a function of analysis of user data can be challenging. Under some circumstances, accurately selecting and recommending compatible elements may be of utmost importance. Incorrect selection of compatible elements may lead to error and user dissatisfaction. SUMMARY OF THE DISCLOSURE In an aspect, a system for using artificial intelligence to analyze user activity data, the system including a computing device, wherein the computing device is designed and configured to receive from a user, at least a biological extraction and at least a user activity datum; receive a diagnostic output as a function of the biological extraction; retrieve, from a fingerprint database, at least a datum of user fingerprint data as a function of a compatible element neutralizer; identify a plurality of compatible elements; select at least a compatible element from the plurality of compatible elements as a function of the fingerprint data wherein selecting the at least a compatible element includes retrieving at least a compatible element similarity index value from a compatible element similarity index value database, wherein the at least compatible element similarity index value is a value assigned to a compatible element indicating a degree of similarity between a first compatible element and a second compatible element; and selecting at least a compatible element as a function of the compatible element similarity index value; and present, using a graphical user interface, the at least a compatible element to a user device. In an aspect, a method for using artificial intelligence to analyze user activity data, the method including receiving from a user, by a computing device, at least a biological extraction and at least a user activity datum; receiving, by the computing device, a diagnostic output as a function of the biological extraction; retrieving, by the computing device, from a fingerprint database, at least a datum of user fingerprint data as a function of a compatible element neutralizer; identifying, by the computing device, a plurality of compatible elements; selecting, by the computing device, at least a compatible element from a plurality of compatible elements as a function of the fingerprint data wherein selecting the at least a compatible element includes: retrieving at least a compatible element similarity index value from a compatible element similarity index value database, wherein the at least compatible element similarity index value is a value assigned to a compatible element indicating a degree of similarity between a first compatible element and a second compatible element; and selecting at least a compatible element as a function of the compatible element similarity index value; and presenting by the computing device, using a graphical user interface, the at least a compatible element to a user device. These and other aspects and features of non-limiting embodiments of the present invention will become apparent to those skilled in the art upon review of the following description of specific non-limiting embodiments of the invention in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS For the purpose of illustrating the invention, the drawings show aspects of one or more embodiments of the invention. However, it should be understood that the present invention is not limited to the precise arrangements and instrumentalities shown in the drawings, wherein: FIG. 1 is a block diagram illustrating an exemplary embodiment of a system for using artificial intelligence to analyze user activity data; FIG. 2 is a block diagram illustrating an exemplary embodiment of a diagnostic engine; FIG. 3 is a block diagram illustrating embodiments of data storage facilities for use in disclosed systems and methods; FIG. 4 is a block diagram illustrating an exemplary embodiment of a biological extraction database; FIG. 5 is a block diagram illustrating an exemplary embodiment of an expert knowledge database; FI