Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing decision systems. In some implementations, methods can include receiving a component request specifying a maximum number of digital components that are capable of being presented on a particular electronic document being rendered at a client device. A ranking score for the given digital component is determined based on a maximum interaction increase factor of formatting available to be applied to the given digital component, the current eligibility value, and the historical eligibility value data. The given digital component is ranked among other available digital components based on the determined ranking score. The given digital component is selected for distribution based on the ranking score of the given digital component being included in the maximum number of highest ranked digital components. The given digital component is transmitted to a client device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining an adjusted requirement for transmission of a given digital component. In one aspect, a system includes a damping subsystem that obtains, from an evaluation subsystem, a standard requirement for transmission of the given digital component. The damping subsystem also obtains, from a prediction subsystem, a predicted requirement for transmission of the given digital component. The damping subsystem determines whether a damping condition is met. When the damping condition is met, the damping subsystem determines the adjusted requirement based on at least the predicted requirement. When the damping condition is not met, the damping subsystem determines the adjusted requirement based on at least the standard requirement.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium.

Abstract: The subject matter of this specification can be embodied in, among other things, a method that includes receiving a request for content to fill a block, the request including information about a size of the block and criteria for identifying eligible content items for inclusion in the block, determining a number of content items to be included in the block, including determining amounts of dynamic resizing to apply to content items, determining an estimate of a difference in conversion rates conditional on receiving an interaction in the different configurations that perform differing amounts of dynamic resizing, and applying the estimate when determining an efficiency for a number of permutations of allocations of eligible content items, establishing a price to be charged to each content sponsor associated with a permutation that has a highest efficiency, and providing the eligible content items and charging the content sponsors based on the established prices.

Abstract: Systems and methods of the present disclosure can provide an improved user experience on client devices selecting to receive context-based third-party content by reducing the number of third-party content items presented for display on such client devices. A data processing system can be configured to employ an auction mechanism with selection criterion thresholds (such as minimum bid values) that result, when used in auctions, in enforcing a limit on the amount of third-party content presented for display on client devices that have selected to receive context-based third-party content. The selection criterion thresholds can result, when used in auctions, in enforcing minimum revenues for publishers. The selection criterion thresholds can be determined offline based on historical statistical parameters.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for evaluating content item configurations are disclosed. In one aspect, a method includes receiving a request for content items to be presented in at least some of two or more presentation positions of a resource. Position factors are obtained for two or more different content item configurations. Based at least in part on the position factors, a preferred content item configuration is selected. A determination is made that the position factor for a particular presentation position increases as the number of presentation positions increases. In response to the determination that the position factor increases, a reserve price is determined for each available presentation position. A number of content items that will be provided is determined based on a number of the reserve prices that are met by bids associated with content items.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for distributing content items are disclosed. In one aspect, a method includes accessing a scaling factor value and accessing a first page value range specifying at least a high page value and a low page value. A determination is made that a first ranking of content items based on the high page value does not match a second ranking of the content items that is based on the low page value. In response to determining that the first ranking does not match the second ranking, an updated first ranking and an updated second ranking are determined based on a second page value range. A determination is made that the updated first ranking matches the updated second ranking. Content items are distributed based on the updated first ranking.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing decision systems. In some implementations, methods can include receiving a component request specifying a maximum number of digital components that are capable of being presented on a particular electronic document being rendered at a client device. A ranking score for the given digital component is determined based on a maximum interaction increase factor of formatting available to be applied to the given digital component, the current eligibility value, and the historical eligibility value data. The given digital component is ranked among other available digital components based on the determined ranking score. The given digital component is selected for distribution based on the ranking score of the given digital component being included in the maximum number of highest ranked digital components. The given digital component is transmitted to a client device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing machine learning systems. In one aspect a method includes determining an average error of a machine learning system (“MLS”). An evaluation function that provides a result that would have been achieved using a specified value of a given parameter is defined. An expected outcome function that provides expected results for prior events based on the error of the MLS is defined. For each of multiple prior events, a target value of the given parameter is determined, e.g., using the expected outcome function. A model is generated using the MLS based on features of the prior events and the determined target values of the given parameter for the prior events. A value is assigned to the given parameter for a new event based on application of the model to features of the new event.

Abstract: Systems and methods for implementing a ride share platform are provided. One example method includes obtaining a passenger reputation score associated with a passenger requesting a ride. The method includes determining a ride price for the requested ride based at least in part on the passenger reputation score. One example system includes one or more dispatch server computing devices that adjust a base compensation for a candidate driver to provide a ride to a passenger based at least in part on a driver reputation score. The example system communicates an offer to a mobile computing device operated by the candidate driver. The offer enables the candidate driver to assent to or decline to provide the ride to the passenger for the adjusted compensation. Another example system determines a priority order for offering candidate drivers based on value indices that have been adjusted according to candidate driver reputation.

Abstract: Systems and methods of the present disclosure are directed to dynamically allocating content in an interface. Search results including first and second applications are identified responsive to a search query input into an interface of an online electronic application marketplace. A first value generated by displaying the first electronic application in a first slot available on the interface is determined. The first value is based on historical monetization generated from the first electronic application. A first candidate content item is identified for display with the search results. A second value generated by displaying the first candidate content item in the first slot is determined. Based on a comparison of the first value and the second value, the first electronic application is selected for display via the first slot of the interface and the candidate content item is selected for display via a second slot of the interface.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for valuing distribution data. One of the methods includes receiving first information describing a desired market. The method includes receiving second information describing a group of users. The method includes receiving third information describing a competitive environment. The method includes determining a first measure of monetary value associated with providing content items to the group of users without using the second information. The method includes determining a second measure of monetary value associated with providing content items to the group of users using the second information. The method includes calculating a value for the second information based on the first measure and the second measure.

Abstract: A first candidate content item and a second candidate content item are identified. The first candidate content item has a first candidate bid value and the second candidate content item has a second candidate bid value. Subject matter of the first candidate content item is identified and compared with item information of an online marketplace to determine a similarity metric. Based on the similarity metric, the first candidate content item is determined to correspond to the online marketplace. Historical competing bid values from historical online auctions are retrieved. A distribution function is determined corresponding to the second candidate bid value. A subsidy value to apply to the first candidate bid value is provided. A combination of the first candidate bid value and the subsidy value is identified as greater than or equal to the second candidate bid value. The first candidate content item is selected for display.

Abstract: Systems and methods of the present disclosure can provide an improved user experience on client devices selecting to receive context-based third-party content by reducing the number of third-party content items presented for display on such client devices. A data processing system can be configured to employ an auction mechanism with selection criterion thresholds (such as minimum bid values) that result, when used in auctions, in enforcing a limit on the amount of third-party content presented for display on client devices that have selected to receive context-based third-party content. The selection criterion thresholds can result, when used in auctions, in enforcing minimum revenues for publishers. The selection criterion thresholds can be determined offline based on historical statistical parameters.

Abstract: Systems and methods for determining bid adjustments that may result in lower costs and/or increased benefit to content providers, and providing recommendations for adjusting a bidding strategy accordingly, are disclosed. One method includes determining a first marginal cost associated with a first set of one or more of a plurality of auctions for presentation of content items within one or more resources. The marginal costs represents a cost to a content provider associated with an additional action performed in association with the content items presented within the resources. The method further includes determining a second marginal cost associated with a second set of one or more of the plurality of auctions. The method further includes determining whether a difference between the first marginal cost and the second marginal cost exceeds a threshold, and generating a recommendation to adjust a bidding strategy in response to determining the difference exceeds the threshold.

Abstract: Systems and methods of optimizing a configuration of content items for display with an online document are provided. A system can identify from a content database a configuration for the online document and a configuration attribute for the configuration, which can include one or more content item slots. The system can determine a selection factor for the configuration based on the configuration attribute. The system can obtain a bid value for a content item and a click-through attribute for the content item slot of the content item configuration. The system can select the configuration based on the selection factor, the bid values for the content item, and the click-through attributes for the content item slot. The system can authorize the content item slot of the configuration to include a content item. The system can provide the online document with the content item for display by a computing device.

Abstract: A method for setting allocations and prices for an auction including receiving a request for content for presentation in association with one or more presentation opportunities on a publisher site, determining one or more eligible content items based on the received request, determining bids associated with each eligible content item, determining a historical bid distribution for bids that have been identified when selecting content for presentation on the publisher site, determining a risk adjustment parameter that reflects a measure of confidence in the accuracy of the historical bid distribution, conducting an auction including scoring the determined eligible content items based on the historical bid distribution, their respective bids, and the risk adjustment parameter, selecting a winning content item from the eligible content items based on the auction, setting a price for the winning content item, and providing the winning content item in response to the request.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for ranking content items. In one aspect, a method includes identifying, for a content item, a bid value specifying an amount a content item provider is willing to pay for user interaction with the content item. A predicted performance measure is identified for the content item. The predicted performance measure is adjusted based on a weighting factor for the content item. The weighting factor for the content item is indicative of confidence that the predicted performance measure will match an actual performance measure for the content item and can be different than a weighting factor for another content item identified for inclusion in a ranking with the content item. A rank score is determined for the content item using the bid value and adjusted predicted performance measure. The content item is provided based on the rank score.

Abstract: An example process includes determining a first quality metric that is indicative of a quality of an opportunity for distribution of content from a content provider as compared to other content providers, where the first quality metric is based on a first predicted access rate and a second predicted access rate, where the first predicted access rate is based on features that are dependent on the content provider, and where the second predicted access rate is based on features that are independent of the content provider. The example process also includes determining a second quality metric that is based on the first predicted access rate of the content; determining, a weight to apply to the first quality metric and to the second quality metric; and determining a weighted average of the first quality metric and the second quality metric that is based on the weight.