Methods and Apparatus For Serving Relevant Advertisements

Patent metadata

Field	Value
Publication number	US-2019156367-A1
Application number	US-201916258939-A
Country	US
Kind code	A1
Filing date	Jan 28, 2019
Priority date	Sep 24, 2002
Publication date	May 23, 2019
Grant date	—

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.

First claim

What is claimed:

1 . A computer implemented method comprising:
determining, using information extracted from a video, that the video is related to one or more topics based on a frequency of occurrence of content in the video that is related to the one or more topics; identifying targeting data for a content item that is available for presentation with various different videos; determining that the content item is relevant to the video, the determining including:
comparing the identified targeting data for the content item to the determined one or more topics related to the video; and
determining, based on the comparison, that the identified targeting data for the content item and the determined one or more topics for the video match; and
serving the content item based on determining that the identified targeting data for the content item matches the determined one or more topics for the video.

2 . The computer implemented method of claim 1 , wherein determining that the identified targeting data for the content item and the determined one or more topics for the video match comprises:
scoring a similarity between the identified targeting data for the content item and the one or more topics that correspond to the video; and determining that the content item is relevant to the video when the similarity is above a threshold score.

3 . The computer implemented method of claim 1 , wherein determining that the video is related to one or more topics comprises:
obtaining a set of rules that specify weights for each topic of a plurality of topics extracted from the video, with a weight of a topic being a function of a frequency of the topic in the video; generating, based on the set of rules, a term vector that represents weights for the plurality of topics for content that appears within the video; and determining that the video is related to one or more topics based on weights for the one or more topics in the vector meeting a specified threshold.

4 . The computer implemented method of claim 1 , wherein the one or more topics corresponding to the video comprise at least one topic from another resource linked to the video.

5 . The computer implemented method of claim 1 , wherein the one or more topics corresponding to the video comprise anchor text in a link from another resource to the video.

6 . The computer implemented method of claim 1 , wherein the one or more topics corresponding to the video comprise text from queries to a search engine that returned a search result identifying the video.

7 . The computer implemented method of claim 1 , wherein the one or more topics corresponding to the video comprise text from queries to a search engine that is configured to return a search result identifying the video, the search result being subsequently selectable by a user.

8 . The computer implemented method of claim 1 , wherein the identified targeting data is provided by a content provider for the content item and comprises at least one of (A) a keyword and (B) a phrase, and wherein the identified targeting data for the content item is received via a content item campaign entry and management component of a server system.

9 . A non-transitory computer readable medium storing instructions that are executable by one or more processors to perform operations comprising:
determining, using information extracted from a video, that the video is related to one or more topics based on a frequency of occurrence of content in the video that is related to the one or more topics; identifying targeting data for a content item that is available for presentation with various different videos; determining that the content item is relevant to the video, the determining including: comparing the identified targeting data for the content item to the determined one or more topics related to the video; and determining, based on the comparison, that the identified targeting data for the content item and the determined one or more topics for the video match; and serving the content item based on determining that the identified targeting data for the content item matches the determined one or more topics for the video.

10 . The non-transitory computer readable medium of claim 9 , wherein determining that the identified targeting data for the content item and the determined one or more topics for the video match comprises:
scoring a similarity between the identified targeting data for the content item and the one or more topics that correspond to the video; and determining that the content item is relevant to the video when the similarity is above a threshold score.

11 . The non-transitory computer readable medium of claim 9 , wherein determining that the video is related to one or more topics comprises:
obtaining a set of rules that specify weights for each topic of a plurality of topics extracted from the video, with a weight of a topic being a function of a frequency of the topic in the video; generating, based on the set of rules, a term vector that represents weights for the plurality of topics for content that appears within the video; and determining that the video is related to one or more topics based on weights for the one or more topics in the vector meeting a specified threshold.

12 . The non-transitory computer readable medium of claim 9 , wherein the one or more topics corresponding to the video comprise at least one topic from another resource linked to the video.

13 . The non-transitory computer readable medium of claim 9 , wherein the one or more topics corresponding to the video comprise anchor text in a link from another resource to the video.

14 . The non-transitory computer readable medium of claim 9 , wherein the one or more topics corresponding to the video comprise text from queries to a search engine that returned a search result identifying the video.

15 . The non-transitory computer readable medium of claim 9 , wherein the one or more topics corresponding to the video comprise text from queries to a search engine that is configured to return a search result identifying the video, the search result being subsequently selectable by a user.

16 . The non-transitory computer readable medium of claim 9 , wherein the identified targeting data is provided by a content provider for the content item and comprises at least one of (A) a keyword and (B) a phrase, and wherein the identified targeting data for the content item is received via a content item campaign entry and management component of a server system.

17 . 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:
determining, using information extracted from a video, that the video is related to one or more topics based on a frequency of occurrence of content in the video that is related to the one or more topics;
identifying targeting data for a content item that is available for presentation with various different videos;
determining that the content item is relevant to the video, the determining including:
comparing the identified targeting data for the content item to the determined one or more topics related to the video; and
determining, based on the comparison, that the identified targeting data for the content item and the determined one or more topics for the video match; and
serving the content item based on determining that the identified targeting data for the content item matches the determined one o

Assignees

• Google Llc

Inventors

• Dean Jeffrey Adgate
• Harik Georges
• Buchheit Paul

Classifications

• G06Q30/02 Primary

  Marketing; Price estimation or determination; Fundraising · CPC title

• G06Q30/0256 Primary

  User search · CPC title

• G06Q30/0251

  Targeted advertisements · CPC title

• G06F16/951

  Indexing; Web crawling techniques · CPC title

• Y10S707/944

  Business related · CPC title