METHOD AND SYSTEM FOR OPTIMIZED CONTENT ITEM ALLOCATION

1 . A method implemented on a computer having at least one processor, a storage, and a communication platform for allocating advertisements, the method comprising:

receiving an advertisement associated with first criteria;

obtaining a plurality of advertisement exposure opportunities, wherein each of the plurality of advertisement exposure opportunities is associated with second criteria and ordered audience clusters that are previously generated for the advertisement exposure opportunity;

obtaining a predicted performance of each of the ordered audience clusters associated with each of the plurality of advertisement exposure opportunities, wherein the predicted performance is estimated with respect to the first criteria;

identifying at least one audience cluster associated with one or more advertisement exposure opportunities based on the first and second criteria as well as the predicted performance associated with the ordered audience clusters of the plurality of advertisement exposure opportunities; and

allocating the advertisement to the at least one audience cluster.

2 . The method of claim 1 , wherein the second criteria associated with a first advertisement exposure opportunity is different than the second criteria associated with a second advertisement exposure opportunity.

3 . The method of claim 1 , wherein the first criteria includes at least a timing constraint associated with the advertisement, preferred advertisement exposure opportunities where the advertisement seeks to be placed, and an expected performance of the at least one audience cluster with respect to one or more attributes associated with the advertisement.

4 . The method of claim 1 , wherein the second criteria includes at least a media type to be placed on the advertisement exposure opportunity, and a time frame available for placing the media type.

5 . The method of claim 1 , wherein the predicted performance of each of the ordered audience clusters is obtained with respect to one or more attributes associated with the advertisement in accordance with a prediction model.

6 . The method of claim 1 , further comprising:

delivering the advertisement to the at least one audience cluster;

receiving execution information related to the delivering of the advertisement; and

updating the allocating based on the received execution information.

7 . A system for allocating advertisements, the system comprising:

a supply-demand matching unit configured to:

receive an advertisement associated with first criteria,

obtain a plurality of advertisement exposure opportunities, wherein each of the plurality of advertisement exposure opportunities is associated with second criteria and ordered audience clusters that are previously generated for the advertisement exposure opportunity,

obtain a predicted performance of each of the ordered audience clusters associated with each of the plurality of advertisement exposure opportunities, wherein the predicted performance is estimated with respect to the first criteria, and

identify at least one audience cluster associated with one or more advertisement exposure opportunities based on the first and second criteria as well as the predicted performance associated with the ordered audience clusters of the plurality of advertisement exposure opportunities; and

an allocating unit configured to allocate the advertisement to the at least one audience cluster.

8 . The system of claim 7 , wherein the second criteria associated with a first advertisement exposure opportunity is different than the second criteria associated with a second advertisement exposure opportunity.

9 . The system of claim 7 , wherein the first criteria includes at least a timing constraint associated with the advertisement, preferred advertisement exposure opportunities where the advertisement seeks to be placed, and an expected performance of the at least one audience cluster with respect to one or more attributes associated with the advertisement.

10 . The system of claim 7 , wherein the second criteria includes at least a media type to be placed on the advertisement exposure opportunity, and a time frame available for placing the media type.

11 . The system of claim 7 , wherein the predicted performance of each of the ordered audience clusters is obtained with respect to one or more attributes associated with the advertisement in accordance with a prediction model.

12 . The system of claim 7 , further comprising a serving unit configured to deliver the advertisement to the at least one audience cluster, and wherein the supply-demand matching unit is further configured to receive execution information related to the delivering of the advertisement, and wherein the allocating unit is further configured to update the allocating based on the received execution information.

13 . A non-transitory machine-readable medium having information recorded thereon, wherein the information, when read by the machine, causes the machine to perform the following:

receiving an advertisement associated with first criteria;

obtaining a plurality of advertisement exposure opportunities, wherein each of the plurality of advertisement exposure opportunities is associated with second criteria and ordered audience clusters that are previously generated for the advertisement exposure opportunity;

obtaining a predicted performance of each of the ordered audience clusters associated with each of the plurality of advertisement exposure opportunities, wherein the predicted performance is estimated with respect to the first criteria;

identifying at least one audience cluster associated with one or more advertisement exposure opportunities based on the first and second criteria as well as the predicted performance associated with the ordered audience clusters of the plurality of advertisement exposure opportunities; and

allocating the advertisement to the at least one audience cluster.

14 . The non-transitory machine-readable medium of claim 13 , wherein the second criteria associated with a first advertisement exposure opportunity is different than the second criteria associated with a second advertisement exposure opportunity.

15 . The non-transitory machine-readable medium of claim 13 , wherein the first criteria includes at least a timing constraint associated with the advertisement, preferred advertisement exposure opportunities where the advertisement seeks to be placed, and an expected performance of the at least one audience cluster with respect to one or more attributes associated with the advertisement.

16 . The non-transitory machine-readable medium of claim 13 , wherein the second criteria includes at least a media type to be placed on the advertisement exposure opportunity, and a time frame available for placing the media type.

17 . The non-transitory machine-readable medium of claim 13 , wherein the predicted performance of each of the ordered audience clusters is obtained with respect to one or more attributes associated with the advertisement in accordance with a prediction model.

18 . The non-transitory machine-readable medium of claim 13 , wherein the machine is further configured to perform the following:

delivering the advertisement to the at least one audience cluster;

receiving execution information related to the delivering of the advertisement; and

updating the allocating based on the received execution information.