Abstract: Systems, methods, and devices are disclosed herein for spend control in online advertising. Systems include a first plurality of advertisement servers included in a first data center, and a second plurality of advertisement servers included in a second data center. Systems include a performance data aggregator configured to receive performance data characterizing bids placed by the first plurality of advertisement servers and the second plurality of advertisement servers. Systems include a spend control analyzer configured to generate spend control data objects based on an estimate of bidding activity associated with the first data center and bidding activity associated with the second data center. Spend control data objects are capable of configuring advertisement servers to perform advertisement operations within determined budgetary constraints.

Abstract: Disclosed herein are systems, methods, and devices for generating attribution metrics. Systems include a sequential data structure generator configured to generate sequential data structures based on performance data. Each of the sequential data structures characterizes a sequential representation of at least some of a plurality of data events during a first time period. Systems also include an attribution metric generator configured to generate a first plurality of attribution scores and a first plurality of attribution metrics based on a first plurality of dimensions associated with the plurality of data events included in the sequential data structures. Systems further include a resource file generator configured to generate a first resource file that stores data values characterizing the first plurality of attribution metrics. The first resource file is capable of being provided to an advertisement server and being used to generate at least one message including a bid request.

Abstract: Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.

Abstract: At a bid determination platform, an initial sequence having an initial order of software steps for filtering advertisements in response to receiving an advertisement bid request is selected. Until a trigger event occurs, the initial sequence of software steps is implemented in the initial order in response to receiving advertisement bid requests. Implementing the initial sequence comprises automatically tracking a failure (or success) metric and resource requirement metric for each of the software steps. After the trigger event occurs, a first optimum sequence of the software steps is automatically selected in a first optimum order so as to optimize a total resource usage for execution of the software steps. Selecting the first optimum sequence of the software steps in the first optimum order is based on the tracked failure (or success) metric and resource requirement metric for each of the software steps during implementation of the initial sequence.

Abstract: Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.

Abstract: Image-based features may be significantly correlated with click-through rates of images that depict a product, which may provide a more formal basis for the informal notion that good quality images will result in better click-through rates, as compared to poor quality images. Accordingly, an image assessment machine is configured to analyze image-based features to improve click-through rates for shopping search applications (e.g., a product search engine). Moreover, the image assessment machine may rank search results based on image quality factors and may notify sellers about low quality images. This may have the effect of improving the brand value for an online shopping website and accordingly have a positive long-term impact on the online shopping website.

Abstract: Systems, methods, and apparatus are disclosed herein. Systems include a plurality of mappers configured to extract a plurality of sequences from user data. The plurality of sequences includes sequential representations of data events associated with a user and a sub-campaign. The plurality of sequences may identify a sequence of data events having action identifiers corresponding to user actions. Systems also include a plurality of reducers configured to generate, for each sub-campaign, a first set of aggregated numbers identifying sequences including action identifiers, and further configured to generate, for each sub-campaign, a second set of aggregated numbers of sequences not including action identifiers. Systems further include a plurality of servers configured to generate a plurality of probabilistic weights. The plurality of servers is further configured to generate a plurality of performance metrics based on the plurality of probabilistic weights.

Abstract: Disclosed herein are systems, methods, and devices for profiling audience populations of websites. Systems include a data structure generator configured to generate a first plurality of data structures based on reference data characterizing a first plurality of audience profiles associated with a plurality of seed websites. The data structure generator is further configured to generate a second plurality of data structures based on first audience profile data characterizing a second plurality of audience profiles associated with the plurality of seed websites, the first audience profile data being generated by an online advertisement service provider.

Abstract: Disclosed herein are systems, methods, and devices for data quality assessment. Systems include a data aggregator configured to receive third party data and reference data. Third party data characterizes a first plurality of values for a first plurality of data categories associated with users identified based on a first online advertisement campaign. Reference data characterizes a second plurality of values for a second plurality of data categories associated with the users. Systems further include a quality assessment metric generator configured to determine probability metrics based on a comparison of the third party data and the reference data, each probability metric characterizing an accuracy of a third party data provider for each association between a user and a data category identified by the third party data provider. The quality assessment metric generator is further configured to generate a quality assessment metric characterizing an overall accuracy of the third party data provider.

Abstract: In a processing system for facilitating on-line advertising or marketer engagement on physical user devices, a device graph specifies confidence metrics for pairs of a plurality of related devices. Specific stable user identifiers are propagated from a first set of devices to a second set of devices having unstable user identifiers based on the confidence metrics. Each device in the second set of devices are designated with a single one of the stable user identifiers that have been propagated to such device based on the confidence metric or combination of confidence metrics that are associated with such single stable user identifier as compared to other confidence metrics associated with other ones of any stable user identifiers that have been propagated to such device.

Abstract: Image-based features may be significantly correlated with click-through rates of images that depict a product, which may provide a more formal basis for the informal notion that good quality images will result in better click-through rates, as compared to poor quality images. Accordingly, an image assessment machine is configured to analyze image-based features to improve click-through rates for shopping search applications (e.g., a product search engine). Moreover, the image assessment machine may rank search results based on image quality factors and may notify sellers about low quality images. This may have the effect of improving the brand value for an online shopping website and accordingly have a positive long-term impact on the online shopping website.

Abstract: Methods and apparatus for identifying on-line users for advertisement or content targeting are disclosed. Historical user data is obtained in association with user identifiers, which have been unambiguously determined. The historical user data includes event data for one or more on-line user events that have occurred for each user identifier. The historical user data also specify fingerprint vectors of characteristic values that are each associated with specific ones of the user identifiers. A current one of the fingerprint vectors that is ambiguously associated with two or more user identifiers is received. A first user identifier is selected from the associated two or more user identifiers of the current fingerprint vector based on the event data of the historical user data. The selected first user identifier is provided to a server configured to provide advertisement or content based on user profile data that is obtainable for such selected first user identifier.

Abstract: Systems, methods, and devices are disclosed herein for identifying, analyzing, and extending audiences associated with online advertising. Systems include a first processing node configured to generate a first plurality of data categories that includes a plurality of seed data categories. Systems include a query node configured to retrieve a second plurality of data categories that includes a plurality of candidate data categories. Systems include a second processing node configured to generate a plurality of relevance metrics including a relevance metric for each candidate data category based on a comparison between each of the plurality of seed data categories and each of the plurality of candidate data categories. Systems include a third processing node configured to generate a third plurality of data categories that includes at least some of the seed data categories and at least some of the candidate data categories based on the generated plurality of relevance metrics.

Abstract: Methods and apparatus for finding detecting unique on-line users for advertisement or content targeting are disclosed. A bid request with initial fingerprint context data for a user and for content that is requested by such user is received at a bid management system, and the bid request is received with or without a user identifier. At the bid management system, an optimum bid for the bid request is determined based on the initial fingerprint context data for the user and the content. The optimum bid with a reference to an advertisement and a script for obtaining additional fingerprint context data from a device of the user is sent from the bid management system. The additional fingerprint context data is received and a unique user identifier is assigned in association with a combination of the initial and additional fingerprint context data.

Abstract: A metadata extraction machine accesses an image that depicts an item. The item depicted in the image may have an attribute that describes a characteristic of the item and an attribute descriptor that corresponds to the attribute of the item and specifies a value of the attribute. The metadata extraction machine performs an analysis of the image. The analysis may include identifying the attribute descriptor corresponding to the attribute based on image segmentation of the image. The metadata extraction machine transmits a communication to a device of a user based on the identifying of the attribute descriptor corresponding to the attribute of the item depicted in the image.

Abstract: Techniques for identifying prohibited information within an image are described. For example, a machine accesses an image that depicts an item. The image may include prohibited information that is disallowed in accordance with a policy. The machine identifies the prohibited information within the image based on an analysis of the image. The machine initiates a response to the prohibited information based on the identifying of the prohibited information within the image.

Abstract: Systems, methods, and apparatus are disclosed herein for allocating a budget among sub-campaigns of an advertisement campaign. The methods may include retrieving data associated with a plurality of users. The data may include data points and action identifiers associated with each user of the plurality of users. Each data point may identify an interaction between a user and a sub-campaign. Each action identifier may include one or more data values identifying a user action. The methods may also include determining a plurality of performance metrics based on the retrieved data. A performance metric may be determined for each sub-campaign. The methods may further include determining a plurality of allocated budgets based on the plurality of performance metrics. An allocated budget may be determined for each sub-campaign. Moreover, each allocated budget may be a portion of a total budget associated with the advertisement campaign.

Abstract: At a bid determination platform, an initial sequence having an initial order of software steps for filtering advertisements in response to receiving an advertisement bid request is selected. Until a trigger event occurs, the initial sequence of software steps is implemented in the initial order in response to receiving advertisement bid requests. Implementing the initial sequence comprises automatically tracking a failure (or success) metric and resource requirement metric for each of the software steps. After the trigger event occurs, a first optimum sequence of the software steps is automatically selected in a first optimum order so as to optimize a total resource usage for execution of the software steps. Selecting the first optimum sequence of the software steps in the first optimum order is based on the tracked failure (or success) metric and resource requirement metric for each of the software steps during implementation of the initial sequence.

Abstract: Techniques and mechanisms described herein facilitate the dynamic selection of bid price. According to various embodiments, a base bid price may be determined for an advertising opportunity bid request received at a communications interface during a designated time period. A designated bid price may be for the advertising opportunity bid request. The designated bid price may be determined at least in part by applying a bid multiplier value to the base bid price. The bid multiplier value may reflect a target pacing rate associated with the designated time period. A bid placement message may be transmitted via the communications interface. The bid placement message may identify the advertising opportunity bid request and the designated bid price.

Abstract: Techniques and mechanisms described herein facilitate the performance metric based placement of bids. According to various embodiments, a first threshold value for bid placement may be identified. The first threshold value may designate a first threshold performance metric level for advertising opportunity bid requests received during a designated time period. An estimated performance metric may be determined for a designated advertising opportunity bid request received during the designated time period. A bid placement message may be transmitted via a communications interface when the estimated performance metric is greater than the first threshold value. The bid request may identify the designated advertising opportunity bid request and a bid placement value.