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: 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: 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: 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, systems, and apparatus, including computer programs encoded on a computer storage medium, for managing or tracking assets in a geographical area. One method includes providing a plurality of travel routes to a plurality of assets located in a geographical area, wherein each of the plurality of travel routes indicates a route along which a corresponding asset of the plurality of assets is to travel, and wherein the plurality of travel routes are based on an analysis of travel history of one or more of the plurality of assets. The method also includes receiving a request from a client device to travel to a destination in the geographical area. The method further includes determining, by one or more computer processors, one or more travel routes of the plurality of travel routes to the destination, wherein the one or more travel routes use different assets to travel to the destination. The method also includes providing the one or more travel routes to the client device.

Abstract: A method, a system, and an article are provided for detecting bot users of a software application. An example method can include: providing a client application to a plurality of users; obtaining device-based data and application-based data for each user, the device-based data including a description of at least one computer component used to run the client application, the application-based data including a history of user interactions with the client application; aggregating the data to obtain a plurality of bot signals for each user; analyzing the bot signals to detect a bot among the plurality of users; and preventing the bot from accessing the client application.

Abstract: Data associated with one or more engagement events is generated for multiple users. The data associated with the one or more engagement events is aggregated for the users. Performance of one or more advertising campaigns is predicted based on the aggregated data.

Abstract: Detecting and managing fraud in an online system is described. An example computer-implemented method can include obtaining a plurality of signals. Each of the signals may be purported to have been generated by a different client device. The method also includes calculating a summary value for the obtained signals that indicates a measure of similarity between the obtained signals and an expected distribution of signals. The method also includes determining that the summary value represents a statistically significant deviation of the obtained signals from the expected distribution of signals. The method also includes labeling the obtained signals as fraudulently generated based on the statistically significant deviation.

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: A method, a system, and an article are provided for detecting bot users of a software application. An example method can include: providing a client application to a plurality of users; obtaining device-based data and application-based data for each user, the device-based data including a description of at least one computer component used to run the client application, the application-based data including a history of user interactions with the client application; aggregating the data to obtain a plurality of bot signals for each user; analyzing the bot signals to detect a bot among the plurality of users; and preventing the bot from accessing the client application.

Abstract: A method, a system, and an article are provided for determining a value for a cohort of users of a client application. An example method includes: obtaining data for a plurality of users of a client application; developing, using the data, a first predictive model to predict a likelihood that a user of the client application will become a payer; developing, using the data, a second predictive model to predict an amount of revenue generated in the client application by the payer; providing the client application to a plurality of new users; using the first predictive model and the second predictive model to predict an amount of revenue generated by a cohort of the new users; and adjusting, based on the predicted revenue for the cohort, a method of acquiring additional users of the client application.

Abstract: A method, a system, and an article are provided for managing content presentations on a plurality of client devices. An example computer-implemented method includes: obtaining data including a record of the content presentations; aggregating the data to generate a history of content presentations for each client device; providing the history of content presentations for each client device to a plurality of weighting algorithms configured to calculate weights for the content presentations; combining the weights from each weighting algorithm for each client device; attributing, based on the combined weights for each client device, a user action taken on the client device to at least one of the content presentations; and facilitating an adjustment of future content presentations based on the attribution.

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: A method, a system, and an article are provided for acquiring new users of a client application. An example method includes: providing the client application to a group of users; obtaining data related to interactions between the client application and each user; providing the data to a predictive model configured to receive the data as input and provide as output a predicted value for each user; identifying a subset of users for whom the predicted value exceeds a predetermined threshold; for each user in the subset of users, providing an identification of the user to a new user finder; and providing the client application to a new group of users, wherein the new group of users was acquired through the new user finder based on the provided identification of the subset of users.

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 method, a system, and an article are provided for detecting bot users of a software application. An example method can include: providing a client application to a plurality of users; obtaining device-based data and application-based data for each user, the device-based data including a description of at least one computer component used to run the client application, the application-based data including a history of user interactions with the client application; aggregating the data to obtain a plurality of bot signals for each user; analyzing the bot signals to detect a bot among the plurality of users; and preventing the bot from accessing the client application.

Abstract: A method, a system, and an article are provided for developing and using a predictive model for analyzing and creating items of content. An example method includes: providing a plurality of items of content in which each item of content includes an image, a video, and/or a sound; extracting a plurality of features from each item of content; determining a performance indicator for each item of content, wherein the performance indicator provides an indication of user responses to presentations of the item of content; developing a model to predict the performance indicator for each item of content based on the plurality of features; based on the model, determining a sensitivity between the performance indicator and each feature; and developing a new item of content based on the determined sensitivities.

Abstract: A method, a system, and an article are provided for determining a lifetime value of a user of a client application. An example method includes: obtaining data including a history of interactions between a plurality of users and a client application on a plurality of respective client devices; developing, using the data, a first model to predict a likelihood that a new user of the client application will be a payer; developing, using the data, a second model to predict an amount of revenue generated by the new user of the client application; providing the client application to a plurality of new users; using the first model and the second model to predict the likelihood and the revenue for each new user in the plurality of new users; and adjusting, based on the predicted likelihood and the predicted revenue, a method of acquiring additional users of the client application.

Abstract: A method, a system, and an article are provided for assessing and managing the presentation of digital content by a group of publishers. An example computer-implemented method can include: obtaining data including a history of (i) content presentations by a plurality of publishers on a plurality of client devices and (ii) user activity associated with the content presentations on the client devices; determining a touch point journey for each of a plurality of conversion events; calculating one or more first performance indicators for each publisher based on the touch point journeys; calculating one or more second performance indicators for each publisher based on the history of user activity associated with the content presentations; calculating a publisher quality score for each publisher based on the first and second performance indicators; and, based on the calculated scores, facilitating an adjustment of content presentations by the plurality of publishers.

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