Yahoo! Inc.

Sai-Ming Li

R Preston McAfee

Shanmugasundaram Ravikumar

Deepak Agarwal

Mohammad Mahdian

Darshan Vishwanath Kantak

Michael Schwarz

Dz-Mou Jung

Jack Z Xie

David Reiley

According to some example embodiments, a method includes calculating learning values associated with a plurality of listings, at least one of said learning values associated with one of said listings representing a value based, at least in part, on a probability distribution of selections of said listing. The method further includes applying said learning values to ranking scores associated with said listings to provide an updated ranking, and electronically auctioning advertising inventory to purchasers associated with said listings based, at least in part, on said updated ranking.

System and method for exploring new sponsored search listings of uncertain quality

Disclosed are apparatus and methods for apparatus and methods for pricing on-line advertisement inventory. In one embodiment, a method for pricing on-line advertisement inventory includes (i) receiving a request for a price of a new product, wherein the new product includes a plurality of specified characteristics of a type of on-line advertisement display, (ii) providing a sample of new impressions that are predicted to be delivered for such new product, (iii) for each new impression, determining which bookings could be served by such new impression so as to define a set of overlapping bookings, (iv) determining the price of each new impression based on a weighted average of a plurality of prices of such each new impression's corresponding overlapping bookings, (v) determining the price of the new product based on an average of the prices of the new impressions, and (vi) returning the price of the new product for use in a booking negotiation with a potential buyer of such new product.

Estimating on-line advertising inventory value based on contract eligibility information

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Santa Clara, CA, United States of America

Sai-Ming Li