Optimizing ranking functions using click data
AssigneeYahoo! Inc.
InventorsMassimiliano Ciaramita, Vassilis Plachouras, Vanessa Murdock
Life of this patent
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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.
Claims29
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.
A method for optimizing machine-learned ranking functions based on click data, method comprising:
- 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.
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:
- 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.
Dependencies are inferred from the claim text.