OPTIMIZING TARGETED ADVERTISEMENT DISTRIBUTION
First Claim
Patent Images
1. A method for targeted advertisement distribution for a social network including a plurality of users, the method comprising the steps of:
- a) creating a user summary for a user by extracting persona attributes of a user account, the user summary including a plurality of keywords, wherein each keyword is associated with an affiliation weight;
b) generating a promotion summary for each of a plurality of advertisements, each promotion summary including a plurality of keywords, wherein each keyword is associated with an importance weight;
c) selecting an advertisement for the user based on the similarity between the promotion summary for the advertisement and the user summary;
d) assessing a user action in response to the advertisement;
e) updating the user summary based on the user action assessment;
f) updating the user summary based on time dependence;
g) updating the promotion summary based on the user action assessment;
h) iterating through steps c) to g) until a predetermined metric is met.
1 Assignment
0 Petitions
Accused Products
Abstract
An iterative method for optimizing targeted advertisement distribution for a social network including a plurality of users, the method including the steps of creating a user summary for a user by extracting persona attributes of a user account, generating a promotion summary for each of a plurality of advertisements, selecting an advertisement for the user based on the similarity between the promotion summary of the advertisement and the user summary, assessing a user reaction to the advertisement, and updating the user summary and promotion summary based on the user reaction.
67 Citations
45 Claims
-
1. A method for targeted advertisement distribution for a social network including a plurality of users, the method comprising the steps of:
-
a) creating a user summary for a user by extracting persona attributes of a user account, the user summary including a plurality of keywords, wherein each keyword is associated with an affiliation weight; b) generating a promotion summary for each of a plurality of advertisements, each promotion summary including a plurality of keywords, wherein each keyword is associated with an importance weight; c) selecting an advertisement for the user based on the similarity between the promotion summary for the advertisement and the user summary; d) assessing a user action in response to the advertisement; e) updating the user summary based on the user action assessment; f) updating the user summary based on time dependence; g) updating the promotion summary based on the user action assessment; h) iterating through steps c) to g) until a predetermined metric is met. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
-
-
19. A method of targeted advertisement distribution to users of a social network, wherein the method comprises the steps of:
-
a) creating a user summary for each of a plurality of users of the social network, wherein the user summary includes a keyword with an associated affiliation weight; b) generating a promotion summary for the advertisement including a keyword with an associated importance weight; c) determining an audience including a plurality of users with user summaries that satisfy the persona; d) serving the advertisement to a user of the audience; e) assessing the action of the user performed in response to the advertisement; f) updating the user summary of the user based on the action assessment; g) updating the promotion summary based on the action assessment; and h) iterating through steps c) to g) until a predetermined metric is met.
-
- 20. The method of claim 20, wherein the metric is a time constraint.
-
36. A system for targeted advertisement distribution to a user, comprising:
-
an advertisement system that selects an advertisement for a user from a plurality of advertisements, wherein the advertisement is associated with a promotion summary comprising a keyword with an importance weighting and the user is associated with a user summary comprising a keyword with an affiliation weighting, and wherein the advertisement system selects the advertisement based on a similarity score calculated between the promotion summary and the user summary; a user response processor that receives a user response to the advertisement and processes the user response to determine whether the user response is positive or negative; and an optimizer that updates the user summary and the promotion summary based on the user response, wherein the optimizer positively updates the user summary and promotion summary for a positive user response, and negatively updates the user summary and promotion summary for a negative user response. - View Dependent Claims (37, 38, 39, 40, 41, 42, 43, 44, 45)
-
Specification