Multi-component profiling systems and methods

• US 9,607,025 B2
• Filed: 09/23/2013
• Issued: 03/28/2017
• Est. Priority Date: 09/24/2012
• Status: Active Grant

• Current Assignee: Airedites LLC
• Original Assignee: Andrew L. Dirienzo
• Inventors: DiRienzo, Andrew L.
• Primary Examiner(s): Stevens, Robert
• Application Number:
  US14/034,231
• Publication Number:
  US 20140236903A1
• Time in Patent Office: 1,282 Days
• Field of Search: 707/661, 707732-734, 707/736
• US Class Current: 1/1
• CPC Class Codes: G06F 16/113 Details of archiving lifecycle management in storage systems G06F3/0649; backup systems G06F11/1446
• CPC Class Codes: G06F 16/21 Design, administration or maintenance of databases
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/24553 of query operations
• CPC Class Codes: G06F 21/604 Tools and structures for managing or administering access control systems
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A multi-component profile is determined for a person. The profile is determined from the analysis of empirical data gather by the person'"'"'s own digital devices which are used as surveillance devices. Several uses are given for the profile derived and for the PProfile System. One of these uses creates an augmented reality environment for personal interactions.

Claims

1. A computer system, comprising

a communication unit;

wherein the communication unit is configured to receive instances of empirical data from a plurality of digital devices used by a particular person; and

wherein each received instance of empirical data comprises one or more portions of data;

a processing unit; and

a storage unit;

wherein the storage unit contains at least

an assemblage of data comprising a plurality of key items and,

for each key item of the plurality of key items, a corresponding family of items; and

wherein each family of items is associated with its corresponding key item of the plurality of key items with respect to a particular type of human behavior;

wherein the computer system is configured by software to perform a process, the process comprising;

receiving two or more instances of empirical data associated with the person from digital devices used by the person;

identifying the portions of data in each of the received instances of empirical data;

for a particular instance of empirical data of the received instances of empirical data containing text content, comparing identified portions of data of the particular instance of empirical data to key items of the plurality of key items of the assemblage of data and determining which of its identified portions of data match a key item of the plurality of key items of the assemblage of data, wherein the identified portions of data of the particular instance of empirical data comprise text strings of the text content, wherein the key items of the plurality of key items comprise text strings, and wherein determining a match between an identified portion of data of the particular instance of empirical data that is a text string and a key item of the plurality of key items that is a text string comprises determining that that identified portion of data and that key item are the same text string;

for at least one matched key item of the plurality of key items of the assemblage of data that is a text string and that has been matched to a respective text string of the identified portions of data of the particular instance of empirical data, using the corresponding family of items of the at least one matched key item to search for matches between members of the corresponding family of items of the at least one matched key item and the identified portions of data of an other instance of empirical data of the received instances of empirical data; and

correlating the particular instance of empirical data with the other instance of empirical data as being potentially relevant to each other with respect to the particular type of human behavior in response to at least one portion of data of the other instance of empirical data matching a member of the corresponding family of items for the at least one matched key item for the particular instance of empirical data.

2. The computer system of claim 1, wherein the process that the computer system is configured to perform further comprises:

identifying the correlation between the particular instance of empirical data and the other instance of empirical data as a behavior data-point for the particular type of human behavior, wherein the particular type of human behavior is associated with at least one profile component;

identifying the behavior data-point as an indication of the at least one profile component for the person;

archiving the behavior data-point for the indicated at least one profile component; and

assigning a scale value for the indicated at least one profile component in response to one or more archived behavior data-points for the indicated at least one profile component.

3. The computer system of claim 2, wherein, in the process, determining which instances of empirical data are potentially relevant to each other with respect to the particular behavior further comprises:

defining specified types of empirical data as potentially relevant to the particular instance of empirical data;

wherein the specified types of empirical data that are defined as potentially relevant comprise;

facial affect of the person while the person is performing an act resulting in generation of the particular instance of empirical data;

voice affect of the person while the person is performing an act resulting in generation of the particular instance of empirical data;

empirical data that has an associated location that is the same as a location associated with the particular instance of empirical data;

empirical data that elicits the same response, behavior, or proclivity from the person as the particular instance of empirical data;

empirical data that has an associated time that is the same as a time associated with the particular instance of empirical data; and

determining if any of the other received instances of empirical data are of the specified types of empirical data.

4. The computer system of claim 2, wherein the process that the computer system is configured to perform further comprises:

performing the process again for at least one other profile component for the person.

5. The computer system of claim 2, wherein the process that the computer system is configured to perform further comprises:

collecting the at least one profile component for the person and any other profile component for the person that have had a scale value assigned to each of them and the respective scale value; and

labeling the collection of the at least one profile component for the person and any other profile component for the person and the respective scale value for each such profile component for the person as the person'"'"'s profile.

6. The computer system of claim 2, wherein, in the process, the at least one profile component of the person is selected from the group consisting of honesty, integrity, kindness, loyalty, ambitiousness, happiness, faithfulness, shyness, persistence, adventurousness, cooperativeness, self-control, optimism and uprightness.

7. The computer system of claim 2, wherein, in the process, correlating the particular instance of empirical data with other received instances of empirical data is terminated when at least one of the following conditions is met:

an amount of time spent searching reaches a specified amount;

a number of results identified reaches a specified amount;

a number of searches performed reaches a specified number;

a number of potentially relevant instances identified reaches a specified number; and

a number of portions of data used reaches a specified number.

8. The computer system of claim 2, wherein the process that the computer system is configured to perform further comprises at least one of:

using the at least one profile component to assist in matching people in a dating service;

using the at least one profile component and the received empirical data to assist a therapist in psychotherapy of the person;

using the at least one profile component and the received empirical data to assist a therapist in couples therapy involving the person;

using the at least one profile component to assist in a self-improvement program of the person;

using the at least one profile component as part of the person'"'"'s healthcare regime;

using the at least one profile component as part of the criminal justice system;

using the at least one profile component, scrubbed of personal identification data, in sociological studies;

using the at least one profile component, scrubbed of personal identification data, for census studies;

using the at least one profile component to match the person to potential careers;

using the at least one profile component as part of employee recruitment and/or screening;

using the at least one profile component to assist a school counselor in understanding a person'"'"'s needs as a student;

using the at least one profile component to assist a school administrator in obtaining a desired mix of students in a class;

using the at least one profile component as a means of matching the person to a college;

using the at least one profile component as a requirement in a college application;

using the at least one profile component to assist in counseling of parents and the person, wherein the person is a child of the parents;

using the at least one profile component of the person, wherein the person is a child, by a parent as an aid in determining the psychological motives of the child;

using the at least one profile component of the person, wherein the person is a child, to assist in picking a school district for the person;

using the at least one profile component by sport coaches to improve the performance level of the person;

using the at least one profile component as part of the person'"'"'s credit report;

using the at least one profile component to identify whether the person is a potentially dangerous person as part of home land security;

using the at least one profile component during networking parties as a means of bringing together the person and those that meet criteria of the person;

using the at least one profile component as an aid in determining if the person should be selected in a draft of athletes;

using the at least one profile component as a means of better understanding the person'"'"'s response to a poll;

using the at least one profile component as part of a gun permit background check of the person;

using the at least one profile component as a means of helping management to determine the person'"'"'s suitability for particular professional work projects;

using the at least one profile component as part of a resume of the person;

receiving authorization from the person to allow the access of at least some parts of the at least one profile component to a third party;

using the at least one profile component to verify the business portrait of the person or to vet business information that the person has entered into other services;

using the at least one profile component to alert the person in real time that driving behavior of the person is detrimental to safe driving;

using the at least one profile component of the person to verify to another person, in real time, that what the person is saying about character, personality, and relationships of the person is true;

using the at least one profile component for forensic studies;

using the at least one profile component to interact with the person in real time;

using the at least one profile component to determine true talents of the person;

using the at least one profile component, scrubbed of personal identification data and added to the profile components of others, to spot trends in a population as a whole;

using the at least one profile component and the received empirical data to generate messages to at least one of the person, a parent of the person, and law enforcement authorities;

archiving the at least one profile component and the received empirical data for the use of the person;

collecting the at least one profile component and additional profile components of the person into subsets from which to base specialized sub-profiles on; and

using the at least one profile component to determine a depth of a social network of the person.

9. The computer system of claim 2, wherein the process that the computer system is configured to perform further comprises:

generating a profile for the person in response to a collection of scale-valued profile components of the person; and

posting at least a portion of the profile for other persons to view.

10. The computer system of claim 9, wherein the process that the computer system is configured to perform further comprises:

restricting the other persons to a group that satisfies a criteria set by the person.

11. The computer system of claim 1, wherein the process that the computer system is configured to perform further comprises archiving the received instances of empirical data.

12. The computer system of claim 1, wherein the process that the computer system is configured to perform further comprises:

for an additional instance of empirical data of the received instances of empirical data, comparing identified portions of data of the additional instance of empirical data to key items of the plurality of key items of the assemblage of data and determining which of its identified portions of data match a key item of the plurality of key items of the assemblage of data;

for at least one matched key item of the plurality of key items of the assemblage of data for the additional instance of empirical data, using the corresponding family of items of the at least one matched key item for the additional instance of empirical data to search for matches between members of the corresponding family of items of the at least one matched key item for the additional instance of empirical data and the identified portions of data of a further instance of empirical data of the received instances of empirical data; and

correlating the additional instance of empirical data with the further instance of empirical data as being potentially relevant to each other with respect to the particular type of human behavior in response to at least one portion of data of the further instance of empirical data matching a member of the corresponding family of items for the at least one matched key item for the additional instance of empirical data.

13. The computer system of claim 1, wherein the process that the computer system is configured to perform further comprises:

performing the process again after one or more additional instances of empirical data associated with the person are received.

14. The computer system of claim 1, wherein, in the process, at least a portion of the received instances of empirical data associated with the person are obtained without self-report by the person.

15. The computer system of claim 1, wherein, in the process, at least a portion of the received instances of empirical data associated with the person are collected from at least one item selected from the group consisting of a desktop computer, a laptop computer, a tablet, a smartphone, an augmented reality device, an email, a word processor document, a Facebook entry, a Tweet, an internet search, a global positioning system (GPS) device, an entry into a web page, a viewed web page, and a TV watched.

16. The computer system of claim 1, wherein, in the process, at least a portion of the received instances of empirical data associated with the person are obtained from observation of the person without subjecting the person to a controlled stimulus.

17. The computer system of claim 1, wherein, in the process, at least some of the portions of data are a portion of the particular instance of empirical data selected from the group consisting of words, metadata, physiological data, facial and voice affect data, and data about the person'"'"'s actions.

18. The computer system of claim 1, wherein, in the process, at least some of the received instances of empirical data associated with the person comprise data that the person has self-reported.

19. The computer system of claim 1, wherein the process further comprises:

identifying an instance of the particular type of human behavior exhibited by the person by analyzing at least one of the particular instance of empirical data and identified other received instances of empirical data that are correlated with the particular instance of empirical data by having at least one portion of data matching a member of the corresponding family of items for the at least one matched key item for the particular instance of empirical data by using logical rules identified in a database of the computer system for assigning probabilistic membership.

20. The computer system of claim 19, wherein the process that the computer system is configured to perform further comprises:

for an additional instance of empirical data of the received instances of empirical data, comparing identified portions of data of the additional instance of empirical data to key items of the plurality of key items of the assemblage of data and determining which of its identified portions of data match a key item of the plurality of key items of the assemblage of data;

for at least one matched key item of the plurality of key items of the assemblage of data for the additional instance of empirical data, using the corresponding family of items of the at least one matched key item for the additional instance of empirical data to search for matches between members of the corresponding family of items of the at least one matched key item for the additional instance of empirical data and the identified portions of data of other received instances of empirical data; and

correlating the additional instance of empirical data with other received instances of empirical data as being potentially relevant to the additional instance of empirical data with respect to the particular type of human behavior for each of those other received instances comprising at least one portion of data matching a member of the corresponding family of items for the additional instance of empirical data; and

identifying a different instance of the particular type of human behavior exhibited by the person by analyzing at least one of the additional instance of empirical data and identified other received instances of empirical data that are correlated with the additional instance of empirical data by having at least one portion of data matching a member of the corresponding family of items for the at least one matched key item for the additional instance of empirical data by using logical rules identified in the database of the computer system for assigning probabilistic membership.

21. The computer system of claim 1, further comprising:

wherein the assemblage of data further comprises a second plurality of key items and, for each key item of the second plurality of key items, a corresponding associated family of items; and

wherein each family of items is associated with its corresponding key item of the second plurality of key items with respect to a second type of human behavior.

22. The computer system of claim 21, wherein at least one key item of the plurality of key items is contained in the second plurality of key items.

23. The computer system of claim 1, wherein at least one key item of the plurality of key items is contained in its associated family of items.

24. The computer system of claim 1, wherein the process that the computer system is configured to perform further comprises:

for an additional instance of empirical data of the received instances of empirical data, comparing identified portions of data of the additional instance of empirical data to key items of the plurality of key items of the assemblage of data and determining which of its identified portions of data match a key item of the plurality of key items of the assemblage of data;

for at least one matched key item of the plurality of key items of the assemblage of data for the additional instance of empirical data, using the corresponding family of items for the at least one matched key item for the additional instance of empirical data to search for matches between members of the corresponding family of items for the at least one matched key item for the additional instance of empirical data and members of the corresponding family of items for the at least one matched key item for the particular instance of empirical data; and

correlating the particular instance of empirical data with the additional instance of empirical data as being potentially relevant to each other with respect to the particular type of human behavior in response to at least one member of the corresponding family of items for the at least one matched key item for the particular instance of empirical data matching a member of the corresponding family of items for the at least one matched key item for the additional instance of empirical data.

25. The computer system of claim 1, wherein at least one key item of the plurality of key items has more than one corresponding family of items.

26. The computer system of claim 25, wherein each corresponding family of items for the at least one key item is associated with its key item with respect to a different type of human behavior.

27. A computer system, comprising

a communication unit;

wherein the communication unit is configured to receive instances of empirical data from a plurality of digital devices used by a particular person; and

wherein each received instance of empirical data comprises one or more portions of data;

a processing unit;

wherein the processing unit comprises at least one operator interface device; and

a storage unit;

wherein the storage unit contains at least storage for

an assemblage of data comprising a plurality of key items and,

for each key item of the plurality of key items, a corresponding family of items; and

wherein the computer system is configured by software to perform a process, the process comprising;

receiving two or more instances of empirical data associated with the person from digital devices used by the person;

identifying the portions of data in each of the received instances of empirical data;

for a particular instance of empirical data of the received instances of empirical data containing text content, comparing identified portions of data of the particular instance of empirical data to key items of the plurality of key items of the assemblage of data and determining which of its identified portions of data match a key item of the plurality of key items of the assemblage of data, wherein the identified portions of data of the particular instance of empirical data comprise text strings of the text content, wherein the key items of the plurality of key items comprise text strings, and wherein determining a match between an identified portion of data of the particular instance of empirical data that is a text string and a key item of the plurality of key items that is a text string comprises determining that that identified portion of data and that key item are the same text string;

for at least one key item of the plurality of key items of the assemblage of data that is a text string and that has been matched to a respective text string of the identified portions of data of the particular instance of empirical data, using the corresponding family of items of the at least one matched key item to search for matches between members of the corresponding family of items of the at least one matched key item and the identified portions of data of one or more of the other received instances of empirical data; and

identifying pairs of instances of empirical data received from the digital devices used by a person;

wherein a pair is defined as two instances of empirical data, such that,

one member of the pair is the particular instance of empirical data; and

the other member of the pair is one of the other received instances of empirical data that comprises at least one portion of data that has been matched to a member of the family of items corresponding to any of the key items that has been matched to one of the portions of data of the particular instance of empirical data.

28. The computer system of claim 27, wherein the computer system is further configured to allow an operator to populate the assemblage of data with key items and to populate the assemblage of data with a corresponding family of items for each key item.

29. A computer system, comprising

a communication unit;

wherein the communication unit is configured to receive instances of empirical data from digital devices used by a particular person; and

wherein each received instance of empirical data comprises one or more portions of data;

a processing unit;

a storage unit;

wherein the storage unit contains at least

an assemblage of data comprising a plurality of key items; and

for each key item of the plurality of key items, a corresponding family of items; and

an interface unit;

wherein the interface unit is configured to enable an operator to specify the key items and the members of all families of items corresponding to each key item wherein the correspondence between a key item and a family of items defines a particular type of relevance determined by the operator;

wherein the computer system is configured by software to perform a process, the process comprising;

receiving two or more instances of empirical data associated with the person from the digital devices used by the person;

identifying the portions of data in each of the received instances of empirical data;

for a particular instance of empirical data of the received instances of empirical data containing text content, comparing identified portions of data of the particular instance of empirical data to key items of the plurality of key items of the assemblage of data and determining which of its identified portions of data match a key item of the plurality of key items of the assemblage of data, wherein the identified portions of data of the particular instance of empirical data comprise text strings of the text content, wherein the key items of the plurality of key items comprise text strings, and wherein determining a match between an identified portion of data of the particular instance of empirical data that is a text string and a key item of the plurality of key items that is a text string comprises determining that that identified portion of data and that key item are the same text string;

for at least one matched key item of the plurality of key items of the assemblage of data that is a text string and that has been matched to a respective text string of the identified portions of data of the particular instance of empirical data, using the corresponding family of items of the at least one matched key item to search for matches between members of the corresponding family of items of the at least one matched key item and the identified portions of data of an other instance of empirical data of the received instances of empirical data; and

correlating the particular instance of empirical data with the other instance of empirical data as being potentially relevant to each other with respect to the type of relevance defined by the operator in response to at least one portion of data of the other instance of empirical data matching a member of the corresponding family of items for the at least one matched key item for the particular instance of empirical data.