CATEGORY SIMILARITIES
First Claim
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1. A computer-implemented method, comprising:
- for each of a plurality of user identifiers;
identifying event data for a user identifier based on past user sessions associated with the user identifier, the event data specifying events that occurred during the past user sessions;
categorizing each of the events as belonging to one or more vertical categories;
for each vertical category, determining a user identifier interest weight for the user identifier based on the events associated with the vertical category;
generating symmetric association data representative of a symmetric association of a given vertical category with at least one other vertical category based on the user identifier interest weights, the symmetric association being pairs of equal similarity measures where an equal similarity measure is based on a first similarity measure of a first vertical category relative to a second vertical category and a second similarity measure of the second vertical category relative to the first vertical category; and
selecting advertisements for user sessions associated with a user identifier based on the symmetric association data.
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Abstract
Methods, systems, and apparatus for determining similarity measures between vertical categories based on users'"'"' online activities. The similarity measures are symmetric similarity measures based on both a similarity measure of a first vertical category relative to a second vertical category and a similarity measure of the second vertical category relative to the first vertical category.
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Citations
21 Claims
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1. A computer-implemented method, comprising:
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for each of a plurality of user identifiers; identifying event data for a user identifier based on past user sessions associated with the user identifier, the event data specifying events that occurred during the past user sessions; categorizing each of the events as belonging to one or more vertical categories; for each vertical category, determining a user identifier interest weight for the user identifier based on the events associated with the vertical category; generating symmetric association data representative of a symmetric association of a given vertical category with at least one other vertical category based on the user identifier interest weights, the symmetric association being pairs of equal similarity measures where an equal similarity measure is based on a first similarity measure of a first vertical category relative to a second vertical category and a second similarity measure of the second vertical category relative to the first vertical category; and selecting advertisements for user sessions associated with a user identifier based on the symmetric association data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer-implemented method, comprising:
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determining user identifier interest weights for user identifiers in a plurality of vertical categories based on events that occurred during past user sessions for the user identifiers; generating symmetric association data representative of a symmetric association of a vertical category with at least one other vertical category based on the user identifier interest weights, the symmetric association being pairs of equal similarity measures where an equal similarity measure is based on a first similarity measure of a first vertical category relative to a second vertical category and a second similarity measure of the second vertical category relative to the first vertical category; identifying a web page presented on a user device during a user session; identifying a vertical category to which the web page belongs; determining a vertical category similar to the vertical category to which the web page belongs based on the symmetric association data; selecting an advertisement belonging to the determined vertical category; and providing the advertisement for display on the user device. - View Dependent Claims (11, 12, 13)
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14. A system, comprising:
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a user interest module configured to; for each of a plurality of user identifiers; identify event data for a user identifier based on past user sessions associated with the user identifier, the event data specifying events that occurred during the past user sessions; categorize each of the events as belonging to one or more vertical categories; and for each vertical category, determine a user identifier interest weight for the user identifier based on the events associated with the vertical category; a symmetric association module configured to; generate symmetric association data representative of a symmetric association of a vertical category with at least one other vertical category based on the user identifier interest weights, the symmetric association being pairs of equal similarity measures where an equal similarity measure is based on a first similarity measure of a first vertical category relative to a second vertical category and a second similarity measure of the second vertical category relative to the first vertical category; and an advertisement selection module configured to select advertisements for user sessions associated with a user identifier based on the symmetric association data. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21)
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Specification