Abstract: A computer-implemented method and a system are provided for estimating values for user events associated with digital content presentations. An example method includes: providing data having a plurality of targeting features for a plurality of users of a software application; performing regression analyses to generate a first predictive model and a second predictive model, wherein the first predictive model is configured to receive targeting features as input and provide as output a prediction of an amount of revenue generated per payer, and wherein the second predictive model is configured to receive at least one targeting feature as input and provide as output a prediction of a number of payers per user event; using the first and second models to determine a value of a user event for a set of targeting parameters; and facilitating a presentation of content on a plurality of client devices based on the determined value.

Abstract: A method, a system, and an article are provided for detecting and managing anomalies associated with content presentations. An example computer-implemented method can include: obtaining a stream of data including a record of clicks on a plurality of client devices; aggregating the stream of data to generate a batch click stream for each of the client devices; processing the stream of data using a real-time anomaly detector to detect a first anomaly indicating that at least one of the client devices was previously associated with fraudulent clicks; processing each batch click stream using a batch anomaly detector to detect a second anomaly indicating that at least one of the batch click streams includes fraudulent clicks; and facilitating an adjustment of content presentations on the client devices, based on at least one of the detected first anomaly and the detected second anomaly.

Abstract: A method, a system, and an article are provided for detecting and managing anomalies associated with content presentations. An example computer-implemented method can include: obtaining data including a history of content presentations by a plurality of publishers on a plurality of client devices; calculating a plurality of performance indicators for each publisher based on the data, the performance indicators providing a measure of user interactions with the content presented by the publisher; generating a time history of each performance indicator for each of a plurality of time periods; selecting, for each time history, at least one anomaly detector from a plurality of anomaly detectors; detecting an anomaly in at least one time history using the selected at least one anomaly detector; and based on the detected anomaly, facilitating an adjustment of content presentations by the plurality of publishers.

Abstract: The technology disclosed relates to building ensemble analytic rules for reusable operators and tuning an operations monitoring system. In particular, it relates to analyzing a metric stream by applying an ensemble analytical rule. After analysis of the metric stream by applying the ensemble analytical rule, quantized results are fed back for expert analysis. Then, one or more type I or type II errors are identified in the quantized results, and one or more of the parameters of the operators are automatically adjusted to correct the identified errors. The metric stream is further analyzed by applying the ensemble analytical rule with the automatically adjusted parameters.

Abstract: Methods and systems for detecting anomalies in high-frequency time-series are described. The method includes receiving a data stream, detecting one or more candidate anomalies in the data stream via a point anomaly detector, storing the one or more candidate anomalies in a queue to be accessed by a pattern anomaly detector, and determining one or more true anomalies in the data stream via the pattern anomaly detector based at least in part on the one or more candidate anomalies. The one or more true anomalies include a pattern anomaly.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for managing or tracking assets in a geographical area. One method includes receiving one or more first messages from a plurality of assets on one or more first channels of a plurality of channels. The one or more first messages may indicate live geographical locations of the plurality of assets located in a geographical area. The method also includes displaying, via a graphical user interface, the live geographical locations of the plurality of assets on a map of the geographical area. The method further includes receiving on a second channel a message indicating a request from a first user device to travel to a destination. The method further includes determining one or more travel routes to the destination. The one or more travel routes may use different assets to transport the first user device to the destination.

Abstract: The technology disclosed relates to differential analysis of sets of time series pairs. In particular, it relates to building estimators of magnitude of difference between two time series. After the basic estimators are built, they are combined into ensemble estimators using linear or nonlinear prediction models to improve their accuracy. In one application, the ensemble is used for estimating the magnitudes of difference over sets of metric pairs observed from distributed applications and systems running over a computer network. The metric pairs are then ranked in decreasing order of magnitude of difference to guide an operator in prioritizing his root cause analysis of faults, thereby reducing the time-to-resolution of problems.

Abstract: The technology disclosed relates to detecting anomalous behavior of network components in a complex network setting.

Abstract: The technology disclosed relates to building ensemble analytic rules for reusable operators and tuning an operations monitoring system. In particular, it relates to analyzing a metric stream by applying an ensemble analytical rule. After analysis of the metric stream by applying the ensemble analytical rule, quantized results are fed back for expert analysis. Then, one or more type I or type II errors are identified in the quantized results, and one or more of the parameters of the operators are automatically adjusted to correct the identified errors. The metric stream is further analyzed by applying the ensemble analytical rule with the automatically adjusted parameters.

Abstract: A system and method for identifying optimal system architectures for a reference application are provided. The system and method comprise executing a reference application and a plurality of test applications on a current system architecture and sampling performance data for each of the applications. The performance data is used to compute an application signature for each application. A similarity element is derived from the application signatures that illustrates the similarity between each application and every other application. Using a similarity threshold and an algorithm, a subset of test applications that are similar to the reference application are derived.

Abstract: A system for serving advertisements determines the frequency of occurrence for each parameter of a plurality of parameters associated with a plurality of search queries. The plurality of parameters are associated with one or more advertisements. The system stores at least some parameters to a first storage based on the frequency of occurrence of the parameters. The system stores the other parameters to a second storage that has a higher latency than the first storage. When serving advertisements, the system ranks advertisements for delivery based on the parameters stored in the first storage device and the second storage.

Abstract: A system and method for identifying optimal system architectures for a reference application are provided. The system and method comprise executing a reference application and a plurality of test applications on a current system architecture and sampling performance data for each of the applications. The performance data is used to compute an application signature for each application. A similarity element is derived from the application signatures that illustrates the similarity between each application and every other application. Using a similarity threshold and an algorithm, a subset of test applications that are similar to the reference application are derived.

Abstract: A system and method for monitoring the performance and execution flow of a target application and generating a corresponding data model are provided. The system and method comprise attaching to a thread or process of a target application and tracking the execution of subroutines using instrumentation commands. Data representing the execution flow of the various subroutines, subroutine calls, and their performance is gathered and used to generate data models representing the threads and processes of the application. The data models are optionally merged and/or pruned. A visualization of the data models is generated indicating relevant points of interest within the target application's execution flow.

Abstract: A system and method for identifying optimal system architectures for a reference application are provided. The system and method comprise executing a reference application and a plurality of test applications on a current system architecture and sampling performance data for each of the applications. The performance data is used to compute an application signature for each application. A similarity element is derived from the application signatures that illustrates the similarity between each application and every other application. Using a similarity threshold and an algorithm, a subset of test applications that are similar to the reference application are derived.

Abstract: The subject matter disclosed herein relates to alter an expression of executable instructions via a compiler component for use in ranking of electronic documents.

Abstract: A computer readable medium stores a program for optimization for a search, and has sets of instructions for receiving a first decision tree. The first decision tree includes several nodes, and each node is for comparing a feature value to a threshold value. The instructions are for weighting the nodes within the first decision tree, determining the weighted frequency of a first feature within the first decision tree, and determining the weighted frequency of a second feature within the first decision tree. The instructions order the features based on the determined weighted frequencies, and store the ordering such that values of features having higher weighted frequencies are retrieved more often than values of features having lower weighted frequencies within the first decision tree.

Abstract: The subject matter disclosed herein relates to prefetching data for use in ranking of electronic documents via a document ranking component.

Abstract: A method, apparatus and computer program product for high performance advertisement serving by exploiting processor thread assignments in a processor having multiple threads. The method commences by receiving digital advertisements, an instance of the digital advertisement being associated with a plurality of decision trees (to relate a user to an advertisement), where the evaluation of a decision tree results in a tree score. After determining a number of cores within the processor, the decisions trees are assigned to processor cores or processor threads by iteratively assigning to a next one of the number of cores, a next decision tree, and iteratively accumulating a plurality of the tree scores to form a tree score subtotal. The tree score subtotals can be compared quantitatively to rank a first digital advertisement against a second digital advertisement, and a ranked advertisement displayed to a user. Some decision trees comprise demographic, behavioral and context quantifiers.

Abstract: A system and method for monitoring the performance and execution flow of a target application and generating a corresponding data model are provided. The system and method comprise attaching to a thread or process of a target application and tracking the execution of subroutines using instrumentation commands. Data representing the execution flow of the various subroutines, subroutine calls, and their performance is gathered and used to generate data models representing the threads and processes of the application. The data models are optionally merged and/or pruned. A visualization of the data models is generated indicating relevant points of interest within the target application's execution flow.

Abstract: A system and method for identifying optimal system architectures for a reference application are provided. The system and method comprise executing a reference application and a plurality of test applications on a current system architecture and sampling performance data for each of the applications. The performance data is used to compute an application signature for each application. A similarity element is derived from the application signatures that illustrates the similarity between each application and every other application. Using a similarity threshold and an algorithm, a subset of test applications that are similar to the reference application are derived.