Web searching
First Claim
1. A method for improving relevance of web searches for a query, comprising:
- providing a pre-existing relevance ranking of a plurality of query/uniform resource locator (URL) pairs, respective labels being associated with the plurality of query/URL pairs;
computing a click relevance ranking of the plurality of query/URL pairs based upon user log data comprising user click data; and
identifying and correcting mislabeled query/URL pairs in the pre-existing relevance ranking based upon the click relevance ranking,the user log data comprising;
respective rank associated with a query/URL pair within the plurality of query/URL pairs at one or more times;
respective total numbers of impressions (I) for the rank associated with the query/URL pair; and
respective total numbers of clicks received (C) for the rank associated with the query/URL pair,wherein the click rate (CR) is the sum of the total number of clicks for all ranks associated with the query/URL pair divided by the sum of the total number of impressions for all ranks associated with the query/URL pair, andcomputing the click relevance ranking comprises;
aggregating the user log data by query and URL;
reducing click bias;
creating a click relevance ordering of the plurality of query/URL pairs;
creating a directed acyclic graph of a relevance relationship between the plurality of query/URL pairs; and
mapping the directed acyclic graph into a linear ordering, at least some of one or more of the providing, computing and identifying performed at least in part with a microprocessor.
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Accused Products
Abstract
Mislabeled URLs are identified and corrected based upon a click relevance ranking computed from user data comprising user click information. The click relevance ranking is formed by applying a set of relevance ordering rules to user log data aggregated by query and URL and by mapping the results of the relevance ordering rules into a linear ordering. For a given query, the aggregated user log data comprises a relative total number of impression, a relative total number of clicks received and a rank associated with the query/URL pair at the time of the total number of impressions and total number of clicks received. The click relevance ranking is used to identify and correct mislabeled query/URL pairs of other rankings according to a number of disclosed methods.
57 Citations
16 Claims
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1. A method for improving relevance of web searches for a query, comprising:
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providing a pre-existing relevance ranking of a plurality of query/uniform resource locator (URL) pairs, respective labels being associated with the plurality of query/URL pairs; computing a click relevance ranking of the plurality of query/URL pairs based upon user log data comprising user click data; and identifying and correcting mislabeled query/URL pairs in the pre-existing relevance ranking based upon the click relevance ranking, the user log data comprising; respective rank associated with a query/URL pair within the plurality of query/URL pairs at one or more times; respective total numbers of impressions (I) for the rank associated with the query/URL pair; and respective total numbers of clicks received (C) for the rank associated with the query/URL pair, wherein the click rate (CR) is the sum of the total number of clicks for all ranks associated with the query/URL pair divided by the sum of the total number of impressions for all ranks associated with the query/URL pair, and computing the click relevance ranking comprises; aggregating the user log data by query and URL; reducing click bias; creating a click relevance ordering of the plurality of query/URL pairs; creating a directed acyclic graph of a relevance relationship between the plurality of query/URL pairs; and mapping the directed acyclic graph into a linear ordering, at least some of one or more of the providing, computing and identifying performed at least in part with a microprocessor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A system configured to improve the relevance of web searches for a query comprising:
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a pre-existing relevance ranking component configured to rank a plurality of query/URL pairs associated with a query; a click relevance ranking component configured to rank the query/URL pairs based upon user click data; and a dynamic program configured to identify and correct mislabeled query/URL pairs in the pre-existing relevance ranking based upon the click relevance ranking, the user log data comprising; respective rank associated with a query/URL pair within the plurality of query/URL pairs at one or more times; respective total numbers of impressions (I) for the rank associated with the query/URL pair; and respective total numbers of clicks received (C) for the rank associated with the query/URL pair; wherein the click rate (CR) is the sum of the total number of clicks for all ranks associated with the query/URL pair divided by the sum of the total number of impressions for all ranks associated with the query/URL pair, and the click relevance ranking component configured to; aggregate user log data by query and URL; reduce click bias; create a click relevance ordering of the plurality of query/URL pairs; create a directed acyclic graph of a relevance relationship between the plurality of query/URL pairs; and map the directed acyclic graph into a linear ordering, at least some of one or more of the pre-existing relevance ranking component, click relevance ranking component and dynamic program implemented at least in part with a microprocessor. - View Dependent Claims (14, 15)
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16. A method for improving relevance of web searches for a query, comprising:
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providing a pre-existing relevance ranking of a plurality of query/uniform resource locator (URL) pairs, respective labels being associated with the plurality of query/URL pairs; aggregating user log data by the query and URL, wherein the user log data comprises a total number of clicks (C) and a total number of impressions (I) for the plurality of query/URL pairs; calculating a click rate (CR) and a normalized click rate (NCR) for each of the plurality of query/URL pairs; creating click relevance ordering of an mth and nth query/URL pair comprising utilization of a plurality of click relevance ordering rules comprising;
if Cm≈
Cn and CRm>
CRn and NCRm>
NCRn;
if Im≈
In and CRm>
CRn and NCRm>
NCRn;
if Im≈
In and CRm>
2×
CRn and NCRm≈
NCRn;
if Im≈
In and CRm≈
CRn and NCRm>
2×
NCRn;
if Im>
100 and In>
100 and CRm>
5×
CRn and NCRm>
0.8×
NCRn; and
if CRm>
50×
Cn;wherein m=1;
k, n=1;
k, and k=number of query/URL pairs in user data log;and wherein URLm is more relevant than URLn if any one of the plurality of click relevance ordering rules are satisfied; creating a directed acyclic graph of a relevance relationship between the plurality of query/URL pairs; mapping the directed acyclic graph into a linear ordering; and identifying and correcting mislabeled query/URL pairs in the pre-existing relevance ranking based upon the click relevance ranking, at least some of one or more of the providing, aggregating, calculating, creating click relevance ordering, creating a directed acyclic graph, mapping and identifying performed at least in part with a microprocessor.
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Specification