Determining proximity to topics of advertisements
First Claim
Patent Images
1. A computer-implemented method for determining a proximity between a search query and an advertisement, comprising:
- preliminarily selecting, with one or more processors, an advertisement based on a set of search keywords associated with a search query,determining, with the one or more processors, a set of ad keywords associated with the advertisement;
mapping, with the one or more processors, the ad keywords to at least one keyword cluster, where each keyword cluster is a group of terms related to a topic of the advertisement;
computing a first conditional probability that the ad keywords occur in the at least one keyword cluster;
computing a second conditional probability that the search keywords occur in the at least one keyword cluster; and
determining, with the one or more processors, a topical proximity between the search query and the advertisement from a comparison of the first conditional probability and the second conditional probability.
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Abstract
The present disclosure includes a system and method for determining proximity to topics of content items (e.g., an advertisement or “ad”). In some implementations, a method includes identifying search criteria associated with keywords of a content item. The keywords used in determining whether or not to embed the content item in Web pages including search results. Numerical scores for the search criteria is determined based, at least in part, on a topic of the content item, the numerical score indicative of proximity to the topic of the content item.
66 Citations
22 Claims
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1. A computer-implemented method for determining a proximity between a search query and an advertisement, comprising:
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preliminarily selecting, with one or more processors, an advertisement based on a set of search keywords associated with a search query, determining, with the one or more processors, a set of ad keywords associated with the advertisement; mapping, with the one or more processors, the ad keywords to at least one keyword cluster, where each keyword cluster is a group of terms related to a topic of the advertisement; computing a first conditional probability that the ad keywords occur in the at least one keyword cluster; computing a second conditional probability that the search keywords occur in the at least one keyword cluster; and determining, with the one or more processors, a topical proximity between the search query and the advertisement from a comparison of the first conditional probability and the second conditional probability. - View Dependent Claims (2, 3, 4, 5)
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6. A computer-implemented method for determining a proximity between a content fragment and an advertisement, comprising:
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receiving a content fragment from a user; determining a set of content keywords associated with the content fragment; selecting an advertisement for display to the user based on an initial topical match between the content keywords and the advertisement; determining a set of ad keywords associated with the advertisement; mapping the ad keywords to at least one keyword cluster, where each keyword cluster is a group of terms related to a topic of the advertisement; computing a first probability that the ad keywords occur in the at least one keyword cluster; computing a second probability that the content keywords occur in the at least one keyword cluster; determining a threshold value based in part on at least one of the content keywords and the ad keywords; and determining the topical proximity between the content fragment and the advertisement from the first probability, the second probability, and the threshold value. - View Dependent Claims (7, 8, 9, 10, 11)
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12. A computer system, comprising:
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a computer-readable medium; a network interface; a processor; and a computer program product encoded on the computer-readable medium that causes the processor to perform operations comprising; receiving a content fragment from a user; determining a set of content keywords associated with the content fragment; selecting an advertisement for display to the user based on an initial topical match between the content keywords and the advertisement; determining a set of ad keywords associated with the advertisement; mapping the ad keywords to at least one keyword cluster, where each keyword cluster is a group of terms related to a topic of the advertisement; computing a first probability that the ad keywords occur in the at least one keyword cluster; computing a second probability that the content keywords occur in the at least one keyword cluster; determining a threshold value based in part on at least one of the content keywords and the ad keywords; and determining a topical proximity between the content fragment and the advertisement from the first probability, the second probability function, and the threshold value.
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13. A system for determining proximity to ad topics, comprising:
one or more computers configured to perform operations comprising; preliminarily selecting an advertisement based on a set of search keywords associated with a search query, determining a set of ad keywords associated with the advertisement; mapping the ad keywords to at least one keyword cluster, where each keyword cluster is related to a topic of the advertisement; computing a first conditional probability that the ad keywords occur in the at least one keyword cluster; computing a second conditional probability that the search keywords occur in the at least one keyword cluster; and determining a topical proximity between the search query and the advertisement from a comparison of the first conditional probability and the second conditional probability. - View Dependent Claims (14, 15, 16)
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17. A method for determining proximity to ad topics, comprising:
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identifying, with one or more processors, one or more character strings associated with a topic of a content item; identifying, with one or more processors, one or more search queries, each search query having one or more query terms that are associated with keywords of the content item, the keywords used in determining whether or not to embed the content item in Web pages including search results responsive to the search queries; determining, with one or more processors, one or more metrics of the search queries based, at least in part, on the one or more character strings, the metrics indicating proximity of the query terms of each search query to the topic of the content item; and determining, with one or more processors, whether a subset of the search queries is irrelevant to the topic in accordance with the one or more proximity metrics, where a search query is irrelevant to the topic when the query terms of the search query are not proximate to the topic. - View Dependent Claims (18, 19, 20, 21, 22)
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Specification