IDENTIFICATION OF USERS FOR ADVERTISING PURPOSES

• US 20080300976A1
• Filed: 05/31/2007
• Published: 12/04/2008
• Est. Priority Date: 05/31/2007
• Status: Active Grant

• Current Assignee: Kyndryl Incorporated (Kyndryl Holdings, Inc.)
• Original Assignee: International Business Machines Corporation
• Inventors: Raghunandan, Hulikunta Prahlad
• Granted Patent: US 10,706,429 B2
• Time in Patent Office: Days
• US Class Current: 705/14
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0245 Surveys
• CPC Class Codes: G06Q 30/0251 Targeted advertisements
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0277 Online advertisement

Abstract

A method and system for identifying users for advertising. Users and attributes are identified. First web sites provided by ISPs accessed by the users are identified. First data received from the ISPs include content of the first web sites and user time spent thereon. The first data is analyzed to determine first attribute values indicative of interest in each attribute by each user. Second data received from ISPs include content of second web sites and user time spent thereon. Second attribute values are derived from questionnaires completed by the users, which indicate interest in each attribute by each user. Third attribute values are determined by combining the first attribute values with the second attribute values for each user. The third attribute values are processed to identify users to which a product or service may be advertised. The identified users are communicated to a provider of the product or service.

Claims

1. A method for identifying users for advertising purposes, said method comprising:

identifying a plurality of users and a plurality of attributes, each attribute being a subject, an activity, or a demographic characteristic;

identifying a first network of first web sites of the Internet accessed by the plurality of users, said access to the first web sites provided to the plurality of users by a first at least one Internet Service Provider (ISP);

receiving, from the first at least one ISP, first data comprising content of the first web sites and time data pertaining to when each user of the plurality of users accessed the first web sites;

analyzing the first data to determine first attribute values comprising a first value of each attribute of the plurality of attributes for each user, said first value being indicative of a level of interest in each attribute by each user, said analyzing based on an amount of time spent by each user at each website of the first web sites in relation to the content of each website of the first web sites;

identifying a second network of second web sites of the Internet accessed by the plurality users, said access to the second web sites provided to the plurality of users by a second at least one ISP;

deriving, from questionnaires completed by the plurality of users, second attribute values comprising a second value of each attribute of the plurality of attributes for each user, said second value being indicative of a level of interest in each attribute by each user, attribute values of said second attribute values having been indicated on the questionnaire by the users of the plurality of users for each attribute to which a keyword relevant to the second web sites has been mapped;

determining third attribute values that comprise a third value of each attribute of the plurality of attributes for each user, by combining the first attribute values for each user with the second attribute values for each user;

processing the third attribute values, said processing comprising determining from the third attribute values an identification of a subset of the plurality of users to whom advertising of a product or service may be directed; and

communicating the identification of the subset of the plurality of users to a provider of the product or service.

2. The method of claim 1, wherein the second at least one ISP does not have access to second data from which the second attribute values may be determined, and wherein the second data pertains to said access of the second web sites by the plurality of users.

3. The method of claim 1, wherein the first and second attribute values are each a binary value of 0 or 1, and wherein said determining third attribute values comprise performing a logical OR between corresponding first and second attribute values to determine the third attribute values.

4. The method of claim 1,

wherein the plurality of users consist of N users such that N is at least 2;

wherein the plurality of attributes consist of M attributes such that M is at least 2;

wherein V_nm,1 and V_nm,2 and V_nm,3 respectively denote the attribute value for attribute m of user n for the first, second, and third attribute values, for n=1, 2, . . . N and m=1, 2, . . . , M;

wherein for a function F(V_nm,k) of V_nm,k for n=1, 2, . . . N and m=1, 2, . . . , M and k=1, 2, said determining third attribute values comprises computing V_nm,3 according to;

V_nm,3=W_m,1*F(V_nm,1)+W_m,2*F(V_nm,2);

wherein W_m,k is a weight that acts as a multiplier on F(V_nm,k) for k=1, 2.

5. The method of claim 4, wherein W_m,k varies with both m and k.

6. The method of claim 4, wherein W_m,k varies with m but does not vary with k.

7. The method of claim 4, wherein W_m,k does not vary with m but does vary with k.

8. The method of claim 4, wherein F(V_nm,k) is a linear function of V_nm,k.

9. The method of claim 4, wherein F(V_nm,k) is a nonlinear function of V_nm,k.

10. The method of claim 1, wherein said determining the identification of the subset of the plurality of users to whom the advertising may be directed comprises:

specifying a target profile of an ideal user of the product or service, said target profile comprising at least two target attributes and associated target attribute values, said plurality of attributes comprising the target attributes;

for each user, computing a nearness to the target profile of each user'"'"'s third attribute values as a function of a difference between each target attribute value and the corresponding third attribute value of each user; and

applying nearness criteria to the computed nearness of each user'"'"'s third attributes to the target profile to determine the subset of the plurality of users consisting of all users that satisfy the nearness criteria.

11. The method of claim 10, wherein the method further comprises specifying a threshold difference for each target attribute, and wherein the nearness criteria for each user is that the difference between each target attribute value and the corresponding third attribute value of each user:

does not exceed the specified threshold difference of each target attribute.

12. The method of claim 11, wherein at least two target attributes have a different specified threshold difference.

13. The method of claim 11, wherein all target attributes have a same specified threshold difference.

14. The method of claim 13, wherein the same specified threshold difference is zero.

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

for each user, determining each third attribute whose third attribute value does not differ from the corresponding target attribute value by more than the threshold difference to be a strong attribute; and

specifying a threshold difference (TD) for each target attribute and a threshold ratio (R_T) wherein the nearness criteria for each user comprises a first criterion that the ratio (R) of the number of strong attributes to the total number of target attributes is not less than the specified threshold ratio (R_T).

16. The method of claim 10, wherein the method further comprises:

specifying a first threshold difference (TD1) for each target attribute;

specifying a second threshold difference (TD2) for each target attribute, said second threshold difference (TD2) exceeding the first threshold difference (TD1);

specifying a threshold ratio (R_T);

specifying a strong weight (W_S), a medium weight (W_M), a weak weight (W_W), and a divisor (D) that exceeds the sum of the first weight, the second weight, and the third weight;

for each user, determining each third attribute whose third attribute value does not differ from the corresponding target attribute value by more than the first threshold difference (TD1) to be a strong attribute;

for each user, determining each third attribute whose third attribute value does not differ from the corresponding target attribute value by more than the second threshold difference (TD2), but does differ from the corresponding target attribute value by more than the first threshold difference (TD1), to be a medium attribute;

for each user, determining each third attribute whose third attribute value differs from the corresponding target attribute value by more than the second threshold difference (TD2) to be a weak attribute,

wherein the nearness criteria for each user comprises a first criterion that a ratio (R) of a sum (C) of a first product, a second product, and a third product to the divisor (D) is not less than the specified threshold ratio (R_T),

wherein the first product for each user is a product of the strong weight (W_S) and the number of strong attributes (N_S),

wherein the second product for each user is a product of the medium weight (W_M) and the number of medium attributes (N_M), and

wherein the third product for each user is a product of the weak weight (W_W) and the number of weak attributes (N_W).

17. The method of claim 10, wherein the nearness criteria is subject to a constraint that limits the total number of users to which advertising of a product or service may be directed to a specified or determined maximum number of such users.

18. A computer system comprising a processor and a computer readable memory unit coupled to the processor, said memory unit containing instructions that when executed by the processor perform the method of claim 1.

19. A computer program product, comprising a computer usable storage medium having a computer readable program code embodied therein, said computer readable program code containing instructions that when executed by a processor of a computer system perform the method of claim 1.

20. A process for supporting computer infrastructure, said process comprising providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in a computing system, wherein the code in combination with the computing system is configured to perform the method of claim 1.