Organization system for ad campaigns
First Claim
Patent Images
1. A computer-implemented method comprising:
- receiving targeting keywords for an advertisement campaign, each of the targeting keywords being a keyword with which advertisements in the advertisement campaign is selectively distributed;
assigning, by a computer, each targeting keyword to one or more topic clusters, each targeting keyword being assigned to the one or more topic clusters based on a measure of semantic relatedness between the targeting keyword and a topic to which the topic cluster has been determined relevant, wherein at least some of the targeting keywords are assigned to multiple topic clusters;
for each topic cluster, determining, by a computer and for all possible pairs of targeting keywords for the topic cluster, a semantic distance between targeting keywords in the pair, the semantic distance being determined based at least in part on a measure of similarity between cluster vectors for the targeting keywords in the pair, the cluster vector for each of the targeting keywords in the pair specifying topic clusters to which the targeting keyword was assigned;
identifying, by a computer and based on the semantic distances, semantically related keyword pairs, each semantically related keyword pair being a keyword pair for which the semantic distance is less than a specified semantic distance threshold;
clustering, by a computer, the identified semantically related keyword pairs into a plurality of sets of pair clusters, the clustering being exclusive of the pairs of targeting keywords for which the semantic distance is greater than the specified semantic distance threshold, the clustering being performed according to a hierarchical clustering technique; and
creating, by a computer and based on the clustering, new ad groups for the advertisement campaign, each ad group specifying at least one advertisement that is selectively distributed using a set of the pair clusters.
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Abstract
An automatic account organization tool is provided to organize a large adgroup into smaller adgroups with semantically meaningful names. For example, a set of input keywords is received, semantically related pairs of keywords are identified from the set of input keywords, and hierarchical clustering is applied to the pairs of keywords to identify a set of clusters of keywords, each cluster having semantically related keywords. A name can be determined for each of the clusters.
67 Citations
21 Claims
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1. A computer-implemented method comprising:
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receiving targeting keywords for an advertisement campaign, each of the targeting keywords being a keyword with which advertisements in the advertisement campaign is selectively distributed; assigning, by a computer, each targeting keyword to one or more topic clusters, each targeting keyword being assigned to the one or more topic clusters based on a measure of semantic relatedness between the targeting keyword and a topic to which the topic cluster has been determined relevant, wherein at least some of the targeting keywords are assigned to multiple topic clusters; for each topic cluster, determining, by a computer and for all possible pairs of targeting keywords for the topic cluster, a semantic distance between targeting keywords in the pair, the semantic distance being determined based at least in part on a measure of similarity between cluster vectors for the targeting keywords in the pair, the cluster vector for each of the targeting keywords in the pair specifying topic clusters to which the targeting keyword was assigned; identifying, by a computer and based on the semantic distances, semantically related keyword pairs, each semantically related keyword pair being a keyword pair for which the semantic distance is less than a specified semantic distance threshold; clustering, by a computer, the identified semantically related keyword pairs into a plurality of sets of pair clusters, the clustering being exclusive of the pairs of targeting keywords for which the semantic distance is greater than the specified semantic distance threshold, the clustering being performed according to a hierarchical clustering technique; and creating, by a computer and based on the clustering, new ad groups for the advertisement campaign, each ad group specifying at least one advertisement that is selectively distributed using a set of the pair clusters. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. An apparatus comprising:
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a database storing a plurality of keywords for an advertisement campaign, each keyword specifying a phrase with which an advertisement in the advertisement campaign is selectively distributed; one or more computers configured to interact with the database, and further being configured to perform operations comprising; assigning each targeting keyword to one or more topic clusters based on a measure of semantic relatedness between the targeting keyword and the one or more topic clusters, wherein at least some of the targeting keywords are assigned to multiple topic clusters; for each topic cluster, determining, for all possible pairs of targeting keywords for the topic cluster, a semantic distance between targeting keywords in the pair, the semantic distance being determined based at least in part on a measure of similarity between cluster vectors for the targeting keywords in the pair, the cluster vector for each of the targeting keywords in the pair specifying topic clusters to which the targeting keyword was assigned; identifying, based on the semantic distances, semantically related pairs keyword pairs, each semantically related keyword pair being keyword pair for which the semantic distance is less than a specified semantic distance threshold; clustering the identified semantically related keyword pairs into a plurality of sets of pair clusters, the clustering being exclusive of the pairs of targeting keywords for which the semantic distance is greater than the specified semantic distance threshold, the clustering being performed according to a hierarchical clustering technique; and creating, based on the clustering, new ad groups for the advertisement campaign, each ad group specifying at least one advertisement that is selectively distributed using a set of pair clusters. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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21. An apparatus comprising:
one or more computers including; means for storing a plurality of keywords for an advertisement campaign, each keyword specifying a phrase with which an advertisement in the advertisement campaign is selectively distributed; means for assigning each targeting keyword to one or more topic clusters, each targeting keyword being assigned to the one or more topic clusters based on a measure of semantic relatedness between the targeting keyword and a topic to which the topic cluster has been determined relevant, wherein at least some of the targeting keywords are assigned to multiple topic clusters; means for determining, for all possible pairs of targeting keywords for the topic cluster, a semantic distance between targeting keywords in the pair, the semantic distance being determined based at least in part on a measure of similarity between cluster vectors for the targeting keywords in the pair, the cluster vector for each of the targeting keywords in the pair specifying topic clusters to which the targeting keyword was assigned; means for identifying, based on the semantic distances, semantically related keyword pairs, each semantically related keyword pair being a keyword pair for which the semantic distance is less than a specified semantic distance threshold; means for clustering the identified semantically related keyword pairs into a plurality of sets of pair clusters, the clustering being exclusive of the pairs of targeting keywords for which the semantic distance is greater than the specified semantic distance threshold, the clustering being performed according to a hierarchical clustering technique; and means for creating, based on the clustering, new ad groups for the advertisement campaign, each ad group specifying at least one advertisement that is selectively distributed using a set of the pair clusters.
Specification