Abstract: A computer-implemented method for allocation-free control of online campaigns for distributing online content includes receiving a daily content distribution spending budget and one or more response functions, calculating one or more plant gain estimates based on the one or more response functions, calculating a marginal content distribution spending budget based on the daily content distribution spending budget, generating one or more control signals based on the calculated marginal budget and the calculated one or more plant gain estimates, generating a price control signal based on the generated one or more control signals, and calculating a bid for one or more impressions based on the price control signal.

Abstract: Systems and methods are disclosed for sorting elements, such as bids in an auction environment or marketplace for the display of an advertisement on a web page. According to one implementation, a plurality of elements may be received over a network. For example, the plurality of elements may comprise a plurality of bids, each of which may include, for example, a bid price, a bid allocation, and a bid target. The received set of elements may be recursively partitioned into a plurality of element subsets. For example, the element set may be partitioned about a pivot selected from a sample set of elements chosen from the element set. A subset of elements may be identified from the element set as eligible elements (e.g., bids eligible for selection as a winning bid). Once the set of eligible elements has been identified, the recursive partitioning of elements may be terminated.

Abstract: Allocating bids for providing content within a segmented campaign is controlled to ensure that an event rate associated with the provided content meets or exceeds a threshold rate. A campaign-level event rate, associated with the provided content, is estimated and provided as a feedback signal. This feedback signal is employed to dynamically update bid allocations for each of the segments, which in turn varies the number or rate of provided impressions and events. Such feedback enables the control of the campaign-level rate and ensures that the campaign-level rate meets or exceeds the rate threshold. To control these rates, the number of total impressions, as well as the number of associated events, is temporally sampled across the campaign segments. Based on the number of impressions and events, the campaign-level event rate is estimated and employed as the feedback signal. Updating the bid allocations may be based on the Beta Distribution.

Abstract: Allocating bids for providing content within a segmented campaign is controlled to ensure that an event rate associated with the provided content meets or exceeds a threshold rate. A campaign-level event rate, associated with the provided content, is estimated and provided as a feedback signal. This feedback signal is employed to dynamically update bid allocations for each of the segments, which in turn varies the number or rate of provided impressions and events. Such feedback enables the control of the campaign-level rate and ensures that the campaign-level rate meets or exceeds the rate threshold. To control these rates, the number of total impressions, as well as the number of associated events, is temporally sampled across the campaign segments. Based on the number of impressions and events, the campaign-level event rate is estimated and employed as the feedback signal. Updating the bid allocations may be based on the Beta Distribution.

Abstract: A computer-implemented method for optimizing electronic content delivery for non-measurable users includes receiving a feature vector for each electronic content impression opportunity, receiving a feature vector for each delivered item of electronic content for measurable users, receiving an in-target indication for each delivered item of electronic content for measurable users, estimating a probability that an electronic content impression opportunity with a specified feature vector will meet targeting requirements based on the received feature vectors and the received in-target indications, receiving an in-target threshold value, generating an in-target rate control signal based on a number of total delivered items of electronic content for measurable users and a number of in-target delivered items of electronic content for measurable users, determining whether the estimated probability is greater than the in-target rate control signal, and generating conditions for delivering a new item of electronic cont

Abstract: Systems and methods are provided for controlling an online advertising campaign. In one embodiment, a computer-implemented method for controlling an online advertising campaign includes receiving a feedback signal reflecting delivery of the online advertising campaign, and comparing the feedback signal to a delivery reference to generate a campaign level control signal. The method further includes receiving a maximum impression bid price for an inventory unit of the online advertising campaign, the maximum bid price for the at least one inventory unit being set by a user, and calculating, using at least one processor, at least a final bid price based on the maximum bid price, on the campaign level control signal, and on an optimization objective for the online advertising campaign, the optimization objective being set by the user. The method also includes submitting, to an electronic market and based on the calculated final bid price, a bid on an impression from the inventory unit.

Abstract: A computer-implemented method for allocation-free control of online campaigns for distributing online content includes receiving a daily content distribution spending budget and one or more response functions, calculating one or more plant gain estimates based on the one or more response functions, calculating a marginal content distribution spending budget based on the daily content distribution spending budget, generating one or more control signals based on the calculated marginal budget and the calculated one or more plant gain estimates, generating a price control signal based on the generated one or more control signals, and calculating a bid for one or more impressions based on the price control signal.

Abstract: Systems and methods are provided for controlling an online advertising campaign. In one embodiment, a computer-implemented method for controlling an online advertising campaign includes receiving a feedback signal reflecting delivery of the online advertising campaign, and comparing the feedback signal to a delivery reference to generate a campaign level control signal. The method further includes receiving a maximum impression bid price for an inventory unit of the online advertising campaign, the maximum bid price for the at least one inventory unit being set by a user, and calculating, using at least one processor, at least a final bid price based on the maximum bid price, on the campaign level control signal, and on an optimization objective for the online advertising campaign, the optimization objective being set by the user. The method also includes submitting, to an electronic market and based on the calculated final bid price, a bid on an impression from the inventory unit.

Abstract: A computer-implemented method for allocation-free control of online campaigns for distributing online content includes receiving a daily content distribution spending budget and one or more response functions, calculating one or more plant gain estimates based on the one or more response functions, calculating a marginal content distribution spending budget based on the daily content distribution spending budget, generating one or more control signals based on the calculated marginal budget and the calculated one or more plant gain estimates, generating a price control signal based on the generated one or more control signals, and calculating a bid for one or more impressions based on the price control signal.

Abstract: Embodiments are directed at determining a conversion rate and a latency distribution for an online campaign. The conversion rate indicates a ratio of an overall number of converted impressions to the number of previously provided impressions. The converted impressions are a subset of the set of previously provided impressions. One method includes receiving conversions from the campaign and determining an observed latency for the conversions. Each conversion is uniquely associated with one of the converted impressions. The observed latencies are based on a temporal difference between the conversion and the associated converted impression. The method simultaneously determines each of the conversion rate and parameters of the latency distribution. The latency distribution indicates a temporal distribution of the observed latencies.

Abstract: Moments of interest of an event may be automatically detected, encoded as snippets, and distributed to users subscribed to a channel of this event. In various embodiments, a moment of interest of an event is to be automatically detected, e.g., based on a near real-time cue on a social network or features in the event transmission. Further, a snippet can be encoded from the transmission of the event based on the detected moment of interest. The snippet may be put on a market place to be bid by various content distributors. Eventually, the snippet may be distributed to an interested user, e.g., via a channel subscribed by the user. Other embodiments may be described and/or claimed.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed at controlling an advertising campaign. In embodiments, a method includes receiving a desired cost indicator. The desired cost indicator can indicate an average cost per unit a user would like to stay below for a current portion of an advertising campaign. The method can further include monitoring bid transactions of an advertising market associated with the advertising campaign to determine an observed cost measurement from the bid transactions. Based, at least in part, on the desired cost indicator and the observed cost measurement, a price control may be determined that can be utilized to adjust a bid price for the advertising campaign. Other embodiments may be described and/or claimed herein.

Abstract: Embodiments are directed at controlling an online advertising campaign to minimize the effective cost per event or impression. Such embodiments include receiving a desired pacing indicator and a maximum cost indicator. The desired pacing indicator indicates a desired pacing that a user would like to achieve in the campaign. The maximum cost indicator indicates a maximum cost per event or impression the user would like to stay below in the campaign. Embodiments further include monitoring bid transactions of an advertising market of the campaign. Based on monitored bid transactions, an observed pacing measurement and/or an observed cost measurement is determined. Price and allocation control signals are determined based on the desired pacing indicator, the maximum cost indicator, the observed pacing measurement, and the observed cost measurement. The control signals are utilized to adjust a bid price and/or a bid allocation for the campaign.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed at cost estimation. In embodiments, a method may include receiving an observed event volume and an observed revenue in the current logical interval for a campaign. The method may also include tracking state information of various revenue state variables and events per revenue state variables associated with the previous logical interval. In addition, the method may include determining a cost estimate for a present logical interval of the campaign based on the state information, the observed event volume, the observed revenue, and an events per revenue forgetting factor. Other embodiments may be described and/or claimed herein.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed at adaptive representation of a control/volume relationship. In embodiments, a method may include receiving, from a control system, a request for control/volume relationship information of a target event for a tactic group. In response, a representation of a control/volume curve can be generated. The representation of the control/volume curve can include a number of control segments. In embodiments, the control segments included within the representation of the control/volume curve are determined based, at least in part, on one or more configuration parameters. The resulting representation of the control/volume curve can then be transmitted to a control system. Other embodiments may be described and/or claimed herein.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed at adaptive representation of a price/volume relationship. In embodiments, a method may include receiving, from a campaign control system, a request for price/volume information. The request may include an identifier of an audience which is targeted by the campaign control system. The method may continue by generating a representation of a price/volume curve based on previously collected price/volume data for the target audience. In some embodiments, adjacent prices included within the representation are determined based on a change in volume between the adjacent prices. The representation can then be output to the campaign control system to enable the campaign control system to determine an initial bid calculated to achieve a desired pacing based on the representation. Other embodiments may be described and/or claimed herein.

Abstract: A method for monitoring an advertising campaign is disclosed and includes receiving a campaign transaction signal, generating a discrete function based on the signal, and generating a continuous function based on the discrete function. The signal indicates a price and an event rate for impressions in the campaign. The discrete function indicates a discrete cumulative distribution of the impressions. The price dimension corresponds to an impression price independent variable. The event rate dimension corresponds to an event rate independent variable. The price dimension and the rate dimension are segmented into a plurality of bins based on threshold values. The continuous function indicates a continuous cumulative distribution of the impressions and is continuous in the price dimension and the rate dimension. The response function is also a continuous function. The response function is a function of control variable that parameterizes a correspondence between the price and event rate variables.

Abstract: Systems, methods, and computer-readable media are disclosed for calculating input-output relationships using, for example, spline functions. In accordance with one implementation, a computer-implemented method is provided that includes determining at least one price-volume point comprising a price and associated volume, transforming the price, and using the transformed price to calculate values along a spline function to obtain a price-volume curve weight factor. The method further includes transforming a second price, calculating values along the spline function and the first derivative of the spline function using the transformed second price to obtain a volume estimate and volume rate at the second price, and recalculating the spline function based on the calculated price-volume curve weight factor, volume estimate, volume estimate and volume rate.

Abstract: Systems and methods are provided for controlling an online advertising campaign. In one embodiment, a computer-implemented method for controlling an online advertising campaign includes receiving a feedback signal reflecting delivery of the online advertising campaign, and comparing the feedback signal to a delivery reference to generate a campaign level control signal. The method further includes receiving a maximum impression bid price for an inventory unit of the online advertising campaign, the maximum bid price for the at least one inventory unit being set by a user, and calculating, using at least one processor, at least a final bid price based on the maximum bid price, on the campaign level control signal, and on an optimization objective for the online advertising campaign, the optimization objective being set by the user. The method also includes submitting, to an electronic market and based on the calculated final bid price, a bid on an impression from the inventory unit.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed at adaptive representation of a control/volume relationship. In embodiments, a method may include receiving, from a control system, a request for control/volume relationship information of a target event for a tactic group. In response, a representation of a control/volume curve can be generated. The representation of the control/volume curve can include a number of control segments. In embodiments, the control segments included within the representation of the control/volume curve are determined based, at least in part, on one or more configuration parameters. The resulting representation of the control/volume curve can then be transmitted to a control system. Other embodiments may be described and/or claimed herein.