Methods and Apparatus For Serving Relevant Advertisements
AssigneeGoogle Inc.
InventorsJeffrey Adgate Dean, Georges Harik, Paul Buchheit
Life of this patent
Estimating the term…
Abstract
The relevance of advertisements to a user's interests is improved. In one implementation, the content of a web page is analyzed to determine a list of one or more topics associated with that web page. An advertisement is considered to be relevant to that web page if it is associated with keywords belonging to the list of one or more topics. One or more of these relevant advertisements may be provided for rendering in conjunction with the web page or related web pages.
Claims21
-19. (canceled)
A computer implemented method comprising:
- obtaining a set of rules that specify weights for each term of a plurality of terms extracted from a resource, with a weight of a term being a function of a frequency of the term in the resource;
- extracting a plurality of terms from a target resource;
- generating, based on the set of rules, a term vector that represents weights for the plurality of terms that appear within the target resource;
- determining that one or more terms of the term vector have one or more respective weights that each exceed a defined threshold;
- identifying targeting data for a content item;
- determining whether the content item is relevant to the target resource by comparing the targeting data for the content item to the determined one or more terms of the term vector;
- and
- serving the content item based on determining that the content item is relevant to the target resource.
A non-transitory computer readable medium storing instructions that are executable by one or more processors to perform operations comprising:
- obtaining a set of rules that specify weights for each term of a plurality of terms extracted from a resource, with a weight of a term being a function of a frequency of the term in the resource;
- extracting a plurality of terms from a target resource;
- generating, based on the set of rules, a term vector that represents weights for the plurality of terms that appear within the target resource;
- determining that one or more terms of the term vector have one or more respective weights that each exceed a defined threshold;
- identifying targeting data for a content item;
- determining whether the content item is relevant to the target resource by comparing the targeting data for the content item to the determined one or more terms of the term vector;
- and
- serving the content item based on determining that the content item is relevant to the target resource.
A computer implemented method comprising:
- obtaining a set of rules that specify weights for each term of a plurality of terms extracted from a resource, with a weight of a term being a function of a frequency of the term in the resource;
- extracting a plurality of terms from the target resource;
- generating, based on the set of rules, a term vector that represents weights for the plurality of terms that appear within text of the target resource, wherein the weights are based on at least one of (A) whether the term appears in the text of the target resource more frequently, relative to one or more other terms that each appear less frequently, and (B) whether the term appears less frequently, relative to one or more other terms that each appear frequently, across a collection of resources to which the target resource belongs;
- identifying targeting data for a content item;
- determining whether the content item is relevant to the target resource by comparing the targeting data to determined one or more terms of the term vector;
- and
- serving the content item based on determining that the content item is relevant to the target resource.
A system comprising:
- one or more processing devices;
- and
- at least one non transitory computer readable medium storing instructions operable to cause the one or more processing devices to perform operations comprising:
- obtaining a set of rules that specify weights for each term of a plurality of terms extracted from a resource, with a weight of a term being a function of a frequency of the term in the resource;
- extracting a plurality of terms from a target resource;
- generating, based on the set of rules, a term vector that represents weights for the plurality of terms that appear within the target resource;
- determining that one or more terms of the term vector have one or more respective weights that each exceed a defined threshold;
- identifying targeting data for a content item;
- determining whether the content item is relevant to the target resource by comparing the targeting data for the content item to the determined one or more terms of the term vector;
- and
- serving the content item based on determining that the content item is relevant to the target resource.
Dependencies are inferred from the claim text.