IP Library Granted Patent US 11,288,689
Granted Patent B2
US 11,288,689 · App. 16/928,925 · Granted Mar 29, 2022

System and method of determining user demographic profiles

Inventors: Timothy C. Vanderhook (Newport Beach, CA); Christopher J. Vanderhook (Yorba Linda, CA); Adityavijay B. Rathore (Ahmedabad, IN); Manish H. Patil (Ahmedabad, IN); Nagendra M. N. Sastry (Ahmedabad, IN); Raviratan Arora (Jersey City, NJ); Shanubhog G. Sangameswara (Cupertino, CA)
Assignee: VIANT TECHNOLOGY LLC
G06Q30/0204G06Q30/02H04L29/08072H04L69/329
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Quick Facts
Patent No.
US 11,288,689
App. No.
16/928,925
Granted
Mar 29, 2022
Kind
B2
Abstract

A method determines a user demographic profile of a user that visits one or more websites of a predetermined group of websites. The method includes generating a first record of visits by the user to the websites of the predetermined group of websites. The method further includes providing one or more website profiles comprising demographic characteristics of each website visited by the user of the predetermined group of websites. The method further includes calculating an estimated user demographic profile of the user by using the first record of visits by the user and the one or more website profiles.

Claims (48)

1. A computer-implemented method of providing a data or service comprising:

obtaining web browsing histories of a plurality of users in a user history file;

based on the user history file and the websites visited by the plurality of users, expressing a probability that a particular user of the plurality of users is in a demographic category as a user probability vector; and

providing a data or a service to the particular user based on the probability vector.

2. The computer-implemented method of claim 1 , wherein:

the user history file comprises one line per user.

3. The computer-implemented method of claim 2 , wherein:

each line of the user history file comprises:

a user identification field;

a date of creation field;

a date updated field; and

one or more site identification-count fields, wherein the site identification denotes a website visited by the user, and the count denotes a number of times the user visited the website.

4. The computer-implemented method of claim 1 , wherein the plurality of users are anonymous users.

5. The computer-implemented method of claim 1 , wherein:

the user probability vector comprises fields corresponding to probabilities that the particular user is a member of a gender group and an age group.

6. The computer-implemented method of claim 1 , wherein:

the user probability vector comprises fields corresponding to probabilities that the particular user is a member of a demographic subgroup or combination of demographic subgroups.

7. The computer-implemented method of claim 1 , further comprising:

representing multiple user probability vectors into a user probability table.

8. The computer-implemented method of claim 7 , wherein:

each line of the user probability table corresponds to one user of the plurality of users and provides the user probability vector for the one user.

9. The computer-implemented method of claim 7 , further comprising:

partitioning multiple user probability vectors among multiple user probability tables such that each of the multiple user probability tables does not exceed a threshold size.

10. A system for providing a data or service comprising:

a computer having a memory;

an application executing on the computer, wherein the application:

obtains web browsing histories of a plurality of users in a user history file;

based on the user history file and the web sites visited by the plurality of users, expresses a probability that a particular user of the plurality of users is in a demographic category as a user probability vector; and

provides a data or a service to the particular user based on the probability vector.

11. The system of claim 10 , wherein:

the user history file comprises one line per user.

12. The system of claim 11 , wherein:

each line of the user history file comprises:

a user identification field;

a date of creation field;

a date updated field; and

one or more site identification-count fields, wherein the site identification denotes a website visited by the user, and the count denotes a number of times the user visited the website.

13. The system of claim 10 , wherein the plurality of users are anonymous users.

14. The system of claim 10 , wherein:

the user probability vector comprises fields corresponding to probabilities that the particular user is a member of a gender group and an age group.

15. The system of claim 10 , wherein:

the user probability vector comprises fields corresponding to probabilities that the particular user is a member of a demographic subgroup or combination of demographic subgroups.

16. The system of claim 10 , wherein the application further:

represents multiple user probability vectors into a user probability table.

17. The system of claim 16 , wherein:

each line of the user probability table corresponds to one user of the plurality of users and provides the user probability vector for the one user.

18. The system of claim 16 , wherein the application further:

partitions multiple user probability vectors among multiple user probability tables such that each of the multiple user probability tables does not exceed a threshold size.

Assignments (5)
SECURITY INTEREST Recorded Apr 29, 2026
From: VIANT TECHNOLOGY LLC
To: PNC BANK, NATIONAL ASSOCIATION
Reel/Frame 074521/0933 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 14, 2020
From: VANDERHOOK, TIMOTHY; VANDERHOOK, CHARLES; RATHORE, ADITYAVIJAY B.; PATIL, MANISH H.; SASTRY, NAGENDRA M.N.; ARORA, RAVIRATAN; SANGAMESWARA, SHANUBHOG G.
To: SPECIFIC MEDIA, INC.
Reel/Frame 053208/0089 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 14, 2020
From: SPECIFIC MEDIA LLC
To: TI NEWCO LLC
Reel/Frame 053208/0144 →
CHANGE OF NAME Recorded Jul 14, 2020
From: SPECIFIC MEDIA, INC.
To: SPECIFIC MEDIA LLC
Reel/Frame 053210/0162 →
CHANGE OF NAME Recorded Jul 14, 2020
From: TI NEWCO LLC
To: VIANT TECHNOLOGY LLC
Reel/Frame 053210/0182 →
Continuity (6)
Continuation 15452432 · Mar 7, 2017
Continuation 14298782 · Jun 6, 2014
Division 13633759 · Oct 2, 2012
Continuation 12709401 · Feb 19, 2010
Continuation 11852775 · Sep 10, 2007
Related Publication 20200342473A1 · Oct 29, 2020