Content placement criteria expansion

Patent metadata

Field	Value
Publication number	US-9501572-B2
Application number	US-201213538425-A
Country	US
Kind code	B2
Filing date	Jun 29, 2012
Priority date	Jun 29, 2012
Publication date	Nov 22, 2016
Grant date	Nov 22, 2016

Abstract

Systems and methods of providing information via a computer network are provided. A data processing system can identify a cluster that includes a plurality of online content items having a semantic or user similarity. The data processing system determines a plurality of cluster placement criteria of the cluster, and receives content configured for display with a web page. The content can be associated with the cluster based on the semantic or user similarity. A cluster placement criterion of the plurality of cluster placement criteria can be selected based on a quality metric of the selected cluster placement criterion, and the selected cluster placement criterion can be provided as a supplemental criterion used to select the content for display with the web page.

First claim

What is claimed is:

1. A computer implemented method of providing cluster placement criteria for use to select content for display via a computer network, comprising:
identifying, by a data processing system, a cluster of a plurality of similar online content items based, at least in part, on a semantic similarity of the online content items;
determining a plurality of cluster-placement criteria associated with the cluster, including identifying one or more keywords that are used to control distribution of the online content items in the cluster;
identifying a quality metric of at least one of the plurality of cluster placement criteria, the quality metric including at least one of a click through rate or a conversion rate of the online content items in the cluster when the cluster placement criteria is used to distribute the online content items;
receiving a given content item that is available for display with a web page, the given content item being associated with a content placement criterion;
associating the given content item with the cluster based on at least a semantic similarity between the given content item and the online content items in the cluster;
determining that the content placement criterion differs from at least one of the cluster placement criteria;
in response to determining that the content placement criterion differs from the at least one of the cluster placement criteria, selecting a cluster placement criterion of the plurality of cluster placement criteria as a supplemental placement criterion for the given content item, wherein the selection is based, at least in part, on the quality metric; and
distributing the given content item using the supplemental criterion.

2. The computer implemented method of claim 1 further comprising:
determining that the quality metric satisfies a threshold.

3. The computer implemented method of claim 1 , further comprising:
expanding the cluster to include the given content item.

4. The computer implemented method of claim 1 , further comprising:
determining a quality metric of each of the plurality of cluster placement criteria.

5. The computer implemented method of claim 1 , further comprising:
identifying the semantic similarity of the online content items based at least in part on subject matter of the plurality of online content items.

6. The computer implemented method of claim 1 , further comprising:
associating the given content item with the cluster based at least in part on the content placement criteria.

7. A system of providing cluster placement criteria for use to select content for display via a computer network, comprising:
a data processing system having one or more processors configured to:
define a cluster of a plurality of similar online content items based, at least in part, on, a semantic similarity of the online content items;
determine a plurality of cluster placement criteria associated with the cluster, including identifying one or more keywords that are used to control distribution of the online content items in the cluster;
identify a quality metric of at least one of the plurality of cluster placement criteria, the quality metric including at least one of a click through rate or a conversion rate of the online content items in the cluster when the cluster placement criteria is used to distribute the online content items;
receive a given content item that is available for display with a web page, the given content item being associated with a content placement criterion;
associating the given content item with the cluster based on at a semantic similarity between the given content item and the online content items in the cluster;
determining that the content placement criterion differs from at least one of the cluster placement criteria;
in response to determining that the content placement criterion differs from the at least one of the cluster placement criteria, select a cluster placement criterion of the plurality of cluster placement criteria as a supplemental placement criterion for the given content item, wherein the selection is based on the quality metric; and
distribute the given content item using the supplemental criterion.

8. The system of claim 7 , further comprising the data processing system configured to:
determine that the quality metric satisfies a threshold.

9. The system of claim 7 , further comprising the data processing system configured to:
expand the cluster to include the given content item.

10. The system of claim 7 , further comprising the data processing system configured to:
determine a quality metric of each of the plurality of cluster placement criteria.

11. The system of claim 7 , further comprising the data processing system configured to:
identify the semantic similarity of the online content items based at least in part on subject matter of the plurality of online content items.

12. The system of claim 7 , further comprising the data processing system configured to:
include the given content item in the cluster based at least in part on the content placement criteria.

13. A computer readable storage medium having instructions to provide cluster placement criteria for use to select content for display via a computer network, the instructions comprising instructions to:
identify a cluster of a plurality of similar online content items based, at least in part, on a semantic similarity of the online content items;
determine a plurality of cluster-placement criteria associated with the cluster, including identifying one or more keywords that are used to control distribution of the online content items in the cluster;
identify a quality metric of at least one of the plurality of cluster placement criteria, the quality metric including at least one of a click through rate or a conversion rate of the online content items in the cluster when the cluster placement criteria is used to distribute the online content items;
receive a given content item that is available for display with a web page, the given content item being associated with a content placement criterion;
associate the given content item with the cluster based on at least a semantic similarity between the given content item and the online content items in the cluster;
determine that the content placement criterion differs from at least one of the cluster placement criteria;
in response to determining that the content placement criterion differs from the at least one of the cluster placement criteria, select a cluster placement criterion of the plurality of cluster placement criteria as a supplemental placement criterion for the given content item, wherein the selection is based, at least in part, on the quality metric; and
distribute the given content item using the supplemental criterion.

14. The computer readable storage medium of claim 13 , further comprising instructions to:
expand the cluster to include the given content item.

15. The computer readable storage medium of claim 13 , further comprising instructions to:
identify the semantic similarity of the online content items based at least in part on subject matter of the plurality of online content items.

Assignees

• Rabii Bahman
• Song Xiaodan
• Cui Yingwei
• Google Inc

Inventors

• Rabii Bahman
• Song Xiaodan
• Cui Yingwei

Classifications

• G06F17/30867 Primary

  Physics · mapped topic

• G06F16/9535 Primary

  Search customisation based on user profiles and personalisation · CPC title

• G06F16/9032

  Query formulation · CPC title

• G06F16/9038

  Presentation of query results · CPC title