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A method and system for intelligent adaptive bidding in an automated online exchange network

A bidding and price technology, applied in the field of automated bidding system, can solve the problem of less traffic and achieve the effect of fast calculation

Pending Publication Date: 2020-04-21
AMADEUS S
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Conversely, in low-value campaigns, DSPs may be constrained to bid very conservatively, even though less traffic will subsequently be generated,

Method used

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  • A method and system for intelligent adaptive bidding in an automated online exchange network
  • A method and system for intelligent adaptive bidding in an automated online exchange network
  • A method and system for intelligent adaptive bidding in an automated online exchange network

Examples

Experimental program
Comparison scheme
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Embodiment Construction

[0057] figure 1 is a block diagram illustrating an exemplary networked system 100 including a demand side platform (DSP) server 102 configured to implement a method of bidding for delivery of advertising content according to an embodiment of the present invention. DSP server 102 may comprise a computer system of conventional architecture. In particular, DSP server 102 includes processor 104 as shown. Processor 104 is operably associated with non-volatile memory / storage 106 , eg, via one or more data / address buses 108 as shown. The non-volatile storage device 106 may be a hard drive, and / or may include solid-state non-volatile memory, such as ROM, flash memory, a solid-state drive (SSD), and the like. Processor 104 also interfaces with a volatile storage device 110 , such as RAM, that contains program instructions and transient data related to the operation of DSP server 102 .

[0058] In a conventional configuration, storage device 106 maintains known program and data cont...

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PUM

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Abstract

A computer-implemented method comprises receiving, from an ad exchange server via a data communications network, a message comprising a bid request which includes site information and user informationrelating to an available ad slot. For each offer in ranked list generated, an offer-level estimate of probability of user interaction with the offer is computed. For a combination of offers includedin the ranked list, an ad-level bid price is computed, based on at least the computed offer-level estimates of probability of user interaction, corresponding offer-level interaction revenues, and an aggressiveness parameter. A bid response includes a bid-priced ad which comprises the combination of offers and the ad-level bid price. Machine learning models for predicting behaviour of online usersare able to automatically determine estimates of probability of user interaction with online content elements based upon aggregated behaviour of prior users in similar contexts.

Description

technical field [0001] The present invention relates to automated bidding systems, and in particular to an intelligent, adaptive method and system for generating bid pricing based on predictions of user interaction behavior and variable aggressiveness settings. Embodiments of the present invention employ machine learning models to predict the behavior of online users and can automatically determine the likelihood of a user interacting with online content elements based on the aggregated behavior of previous users in similar contexts. The invention may be applied in an online advertising system, for example, to determine bid prices for serving advertisements to be presented to users, for example via web pages within mobile applications. Background technique [0002] Online (e.g., web-based, mobile, or in-app) advertising differs from traditional media advertising in the degree to which it can personalize audience targeting. For example, while advertising on broadcast media (...

Claims

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Application Information

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IPC IPC(8): G06Q30/02
CPCG06Q30/02G06Q30/0283G06Q30/0273
Inventor R·爱邱纳·阿戈斯特A·R·芒提尼·道里维拉D·雷诺帝
Owner AMADEUS S
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