System and method for low rank field-weighted factorization machine and application thereof in content recommendation
AssigneeYahoo Assets LLC
InventorAlex Shtoff
Life of this patent
Estimating the term…
Abstract
The present teaching relates to online advertising. A diagonal vector d is determined based on supply and demand data identified from ad auction related data. A predicted performance (P-P) metric is computed based on the diagonal vector d via low rank field weighted factorization machines (FwFM) for each of candidate ads included in the ad auction related data. The candidate ads are ranked based on their corresponding P-P metrics. A winning ad is selected from the ranked candidate ads according to a predetermined selection criterion.
Claims20
A method, comprising:
- processing ad auction related data to identify supply data and demand data;
- determining a diagonal vector d based on the supply data and the demand data;
- computing a predicted performance metric via low rank field weighted factorization machines for each of a plurality of candidate ads included in the ad auction related data based on the diagonal vector d;
- ranking the plurality of candidate ads based on their corresponding predicted performance metrics;
- and
- selecting one of the ranked plurality of candidate ads as a winning ad according to a predetermined selection criterion and outputting the winning ad for display via an online platform, so as to support online advertising with real-time performance-based ad ranking and recommendation.
A machine readable and non-transitory medium having information recorded thereon, wherein the information, when read by the machine causes the machine to perform the following steps:
- processing ad auction related data to identify supply data and demand data;
- determining a diagonal vector d based on the supply data and the demand data;
- computing a predicted performance metric via low rank field weighted factorization machines for each of a plurality of candidate ads included in the ad auction related data based on the diagonal vector d;
- ranking the plurality of candidate ads based on their corresponding predicted performance metrics;
- and
- selecting one of the ranked plurality of candidate ads as a winning ad according to a predetermined selection criterion and outputting the winning ad for display via an online platform, so as to support online advertising with real-time performance-based ad ranking and recommendation.
A system, comprising:
- a low rank field-weighted factorization machine (FwFM) predicted performance (P-P) metric determiner implemented by a processor and configured for
- processing ad auction related data to identify supply data and demand data,
- determining a diagonal vector d based on the supply data and the demand data, and
- computing a predicted performance metric via low rank FwFM for each of a plurality of candidate ads included in the ad auction related data based on the diagonal vector d;
- a P-P metric based ad ranking unit implemented by a processor and configured for ranking the plurality of candidate ads based on their corresponding predicted performance metrics;
- and
- a winning ad selection unit implemented by a processor and configured for selecting one of the ranked plurality of candidate ads as a winning ad according to a predetermined selection criterion and an output device implemented by a processor and configured for outputting the winning ad for display via an online platform, supporting online advertising with real-time performance-based ad ranking and recommendation.
Dependencies are inferred from the claim text.