OPTIMIZING RANKING FUNCTIONS USING CLICK DATA
First Claim
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1. A system for optimizing machine-learned ranking functions based on click data, the system comprising:
- a web server configured to collect click data for a set of queries and results;
an advertisement engine configured to determine weighting for each feature of a plurality of features according to an online learning model based the click data; and
wherein the advertisement engine selects an advertisement from a plurality of advertisements for display on a web page based on the weighting of each feature of the plurality of features.
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Abstract
A system for optimizing machine-learned ranking functions based on click data. The system determines the weighting for each feature of a plurality of features according to a learning model based on the click data. The system selects an element from a plurality of elements for display on a web page based on the weighting of each feature of the plurality of features. The system may rank the items to form a list on the web page based on the weighted features in order of inferred relevance according to the online learning model.
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Citations
29 Claims
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1. A system for optimizing machine-learned ranking functions based on click data, the system comprising:
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a web server configured to collect click data for a set of queries and results; an advertisement engine configured to determine weighting for each feature of a plurality of features according to an online learning model based the click data; and wherein the advertisement engine selects an advertisement from a plurality of advertisements for display on a web page based on the weighting of each feature of the plurality of features. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A method for optimizing machine-learned ranking functions based on click data, method comprising:
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determining weighting for each feature of a plurality of features according to an online learning model based on click data; selecting an element from a plurality of elements for display on a web page based on the weighting of each feature of the plurality of features. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. A computer readable medium having stored therein instructions executable by a programmed processor for optimizing machine-learned ranking functions based on click data, the computer readable medium comprising instructions for:
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determining weighting for each feature of a plurality of features according to an online learning model based on click data; selecting an element from a plurality of elements for display on a web page based on the weighting of each feature of the plurality of features. - View Dependent Claims (26, 27, 28, 29)
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Specification