Abstract: An online system receives information describing a target group of online system users from a third party system and stores the information describing the target group. The online system subsequently uses the target group to select content for presentation to one or more users. For example, users included in the target group are identified as eligible to be presented with content items. Content items are associated with objectives satisfied when a specified interaction with the content item, or with an object associated with the content item, is received. Based on revenue obtained by the online system from presenting content based on the target group as well as interactions satisfying objectives associated with various presented content, the online system determines a monetization value for the target group. Based on the monetization value, the online system determines whether to continue storing the information describing the target group.

Abstract: Technologies for providing streamlined provisioning of accelerated functions in a disaggregated architecture include a compute sled. The compute sled includes a network interface controller and circuitry to determine whether to accelerate a function of a workload executed by the compute sled, and send, to a memory sled and in response to a determination to accelerate the function, a data set on which the function is to operate. The circuitry is also to receive, from the memory sled, a service identifier indicative of a memory location independent handle for data associated with the function, send, to a compute device, a request to schedule acceleration of the function on the data set, receive a notification of completion of the acceleration of the function, and obtain, in response to receipt of the notification and using the service identifier, a resultant data set from the memory sled. The resultant data set was produced by an accelerator device during acceleration of the function on the data set.

Abstract: Methods, systems, and media for dynamically detecting mobile environment information are provided.

Abstract: The present disclosure provides systems and methods for entropy balanced population measurement. Entropy balancing is a statistical technique for preprocessing data to achieve covariate balance. Weighting coefficients may be dynamically adjusted to satisfy balance conditions or constraints to adjust for inequalities in representation, thereby improving covariate moments. Using entropy balancing and linear regression analysis with panel content exposure and results data provides a mechanism to estimate the effects of multiple exposure vectors simultaneously, including instances where panelists are exposed to a vector multiple times. Data may be obfuscated or anonymized for preprocessing via a double-encrypted intersection-based extraction mechanism, allowing both measurement systems and panel providers to retain confidential information.

Abstract: A computer-implemented method of generating a PGM with causal information, said graphical model containing the causal relationship between a first variable and a second variable, the method comprising: receiving data at a processor, said data showing a correlation between the first variable and a second variable; producing a third variable by reducing the dimensionality of the graphical representation of the two dimensional data defined by the first variable and the second variable, determining determine the causal relationship between the first and third variables and the second and third variable, the causal discovery algorithm being able to determine if the first variable causes the third variable, the third variable causes the first variable, the second variable causes the third variable and the third variable causes the second variable; and outputting a graphical model indicating the direction of edges in a graphical representation of said PGM.

Abstract: A computer system may include a server(s) to publish RSS feeds each including a unique ID for an associated audio file. Each audio file may have an action(s) pinned to a respective playback time window within the audio file. A client computing device may cooperate with the server(s) to access a given RSS feed and play the respective audio file, identify the unique ID for the respective audio file from the RSS feed, retrieve the playback time window from the server(s) based upon the unique ID, display a selectable graphical prompt on the display during the playback time window, and send a notification to the server(s) based upon selection of the prompt identifying the unique ID and user-specific information for a user of the client computing device. The server(s) may identify the action(s) associated with the respective audio file based upon the notification, and call a corresponding application based thereon.

Abstract: A method, apparatus and product for identifying a bot agent using behavioral features. The method comprising obtaining a set of behavioral features of a usage of an input device during an interaction of an agent with a page, wherein the set of behavioral features are consistent with a human-generated interaction, wherein the set of behavioral features are generated based on events obtained from a client device used by the agent; automatically estimating whether the agent is a bot based on comparison of the set of behavioral features with one or more additional sets of behavioral features, wherein the one or more additional sets of behavioral features were previously obtained based on interactions of one or more agents with one or more pages; and in response to an estimation that the agent is a bot, performing a responsive action.

Abstract: Systems and methods for scoring promotions are provided. A set of training offers are received, which include combinations of variable values. These combinations of variable values are converted into a vector value. The offers are paired and the vectors subtracted from one another, resulting in a pair vector. Metrics for the success of offers is collected, and are subtracted from one another for the paired offers to generate a raw score. This raw score is then normalized using the pair vector. The normalized scores are utilized to generate a model for the impact any variable value has on offer success, which may then be applied, using linear regression, to new offers to generate an expected level of success. The new scored offers are ranked and the top-ranked offers are selected for inclusion in a promotional campaign.

Abstract: The disclosure relates to a synchronously playing method and device of a media file, and a storage medium, the method includes: creating a media source object corresponding to a playing window in a webpage through a player embedded into the webpage; adding different tracks in the fragmented media file into the same source buffer object in the media source object; transmitting a virtual address taking the media source object as a data source to a media element of the webpage; calling the media element to parse the media source object associated with the virtual address, and reading the tracks in the source buffer object of the associated media source object, and decoding and playing the tracks.

Abstract: A system, comprising: at least one hardware processor; at least one executable software module that, when executed by the hardware processor, performs operations comprising: detecting a first event associated with a contact; in response to detecting the first event: collecting environment data associated with the first event; selecting a first of a plurality of actions based at least in part on the environment data; and performing the first action.

Abstract: Embodiments of the systems and methods disclosed herein provide a sponsor matching system in which players and sponsors can be matched. Upon a match based at least in part on stored sponsorship criteria and/or player preferences, a first sponsor can select a set of players to receive permission to select an advertisement associated with the first sponsor. Once a first player of the selected players selects an advertisement and an advertisement placement location associated with the first sponsor, the sponsor matching system can generate game rendering instructions for a first player system associated with the first player.

Abstract: An online system receives host content items and supplementary content items to be presented in conjunction with one another. In embodiments, the online system receive an allocation of display instances of supplementary content items with host content items during a time interval. For a host content providers, the online system receives a count of display instances of supplementary content items in conjunction with host content items. The online system determines a content quality score based on user interactions with content from the host content provider and a count of display instances for host content items presented in conjunction with supplementary content items for a preceding time interval. The online system determines a content quality threshold based and, for host providers with content quality scored below the threshold, presents host content items in conjunction with supplementary content items to a user.

Abstract: Systems and methods of evaluating information in a computer network environment are provided. A data processing system can obtain or receive a content placement criterion, such as a keyword, associated with a content item and can determine a quality metric of the content placement criterion. The data processing system can identify a candidate content placement criterion and expand placement criteria associated with the content item to include the content placement criterion and the candidate content placement criterion based at least in part on an evaluation of the quality metric of the content placement criterion. The data processing system can expand placement criteria based in part on a throttling parameter. The data processing system can identify a correlation between a document and the placement criteria to identify appropriate content items for the document.

Abstract: Aspects of the subject disclosure may include, for example, a method including obtaining an advertisement package, wherein the advertisement package defines an interactive extended reality advertisement and includes a plurality of optional features; obtaining information about a user, their equipment, and their environment; creating an interactive extended reality advertisement by choosing a selected feature of the plurality of optional features according to the user information; and presenting the interactive extended reality advertisement to the user equipment. Other embodiments are disclosed.

Abstract: Performance-based digital content delivery in a digital medium environment is described. Initially, different items of a collection of digital content are delivered to a substantially equal number of users. The collection is then iteratively tested to identify which content item achieves a desired action (e.g., conversion) at a highest rate. During the iterative test, data describing user interaction with the delivered content is collected. Based on the collected data, measures of achievement are determined for the different content items. Measures of statistical guarantee are also computed that indicate an estimated accuracy of the achievement measures. Responsive to determining that a condition for ending the test has not yet occurred, an optimized allocation is computed for delivery of the content by applying one of multiple allocation optimization techniques. The particular technique applied is based on the condition for ending the test and a type of statistical guarantee associated with the test.

Abstract: A control system and method for controlling a system, which employs a data set representing a plurality of states and associated trajectories of an environment of the system; and which iteratively determines an estimate of an optimal control policy for the system. The iterative process performs the substeps, until convergence, of estimating a long term value for operation at a respective state of the environment over a series of predicted future environmental states; using a complex return of the data set to determine a bound to improve the estimated long term value; and producing an updated estimate of an optimal control policy dependent on the improved estimate of the long term value. The control system may produce an output signal to control the system directly, or output the optimized control policy. The system preferably is a reinforcement learning system which continually improves.

Abstract: The present disclosure describes a system, method, and computer program for automatically predicting the emotion(s) to which a user is most likely to respond based on user characteristics and for tailoring a marketing message to a user based on the predicted emotion(s). A statistical model is created that predicts how a user with certain characteristics will respond to certain emotions. User characteristics are the input to the model, and, for each of a set of emotions, the output is the probability of a corresponding user responding to a message with the emotion. The statistical model is used to generate promotional messages that are tailored to each user based on the emotion to which the user is predicted to respond best, given the user's characteristics.

Abstract: The disclosed embodiments include methods, systems, and articles of manufacture for providing offers for linked transactions. Transaction data corresponding to a first product physically purchased using a financial service account and product identification data identifying the first purchased product are received. The transaction data and the product identification data are associated. A consumer that purchased the first product is determined based on at least the transaction data. Follow-on purchase to offer for sale to the consumer based on the product identification data is determined and a follow-up purchase offer to purchase the follow-on product is generated. The consumer is provided with the follow-on purchase offer to enable the consumer to purchase the follow-on product in an electronic commerce purchase transaction.

Abstract: The invention features a system and method for finely tuning the rate at which ad impressions are delivered to users based on various metrics used to characterize the quality of the ad opportunities. With the present invention, more relevant ads can be selected and delivered to a wide range of recipients while still compensating for the variations in the volume of Internet traffic and usage over the course of the day. The system and method of the present invention employ a plurality of bid boundaries corresponding to different volumes of ad opportunities, thereby enabling the invention to adjust the number of ad opportunities sought over the course of day while consistently targeting the mix of ad opportunities yielding the highest response rates and margin. The bid boundaries are selected in real-time based on the behavior of prior ad recipients. The behavior may include click-through rates or entry into a geo-fence, for example.

Abstract: The present disclosure provides method, apparatus, and storage medium for media file delivery. The method includes: obtaining a target resource consumption and an actual resource consumption of a first media file, one time of delivery of the first media file corresponding to one time of resource consumption; comparing the target resource consumption with the actual resource consumption, to obtain a first comparison result; adjusting, according to the first comparison result, a value of a resource contention parameter of the first media file from a first value to a second value, the resource contention parameter being used for determining a delivery order of the first media file when the first media file participates in a delivery contention; and performing a first delivery operation on the first media file according to the resource contention parameter whose value is the second value.

Abstract: Techniques for predictively selecting a content presentation in a client-server computing environment are described. In an example, a content management system detects an interaction of a client with a server and accesses client features. Responses of the client to potential content presentations are predicted based on a multi-task neural network. The client features are mapped to input nodes and the potential content presentations are associated with tasks mapped to output nodes of the multi-task neural network. The tasks specify usages of the potential content presentations in response to the interaction with the server. In an example, the content management system selects the content presentation from the potential content presentations based on the predicted responses. For instance, the content presentation is selected based on having the highest likelihood. The content management system provides the content presentation to the client based on the task corresponding to the content presentation.

Abstract: An influence system for predicting advertisement impact for campaign selection. For each campaign, an advertising probe campaign is operated by sending an advertisement to each entity in a treatment group of entities. A control group of entities which excludes the treatment group entities is selected and no campaign advertising content is sent to the treatment group entities. An influence model is created for each campaign by comparing features of the respective advertising probe campaign's treatment group converters to features of the control group converters. A campaign is selected for an opportunity to expose a specified entity to advertising based on the result of applying each respective campaign's influence model to features of the specified entity. Advantageously, a campaign operator can make good use of a rare, high quality advertising opportunity by allotting it to an advertising campaign based on a likelihood of influencing the specified entity.

Abstract: Methods, systems and apparatus for calibrating data using relaxed benchmarks constraints are described. An example apparatus for generating a unique solution when calibrating data via a calibration model having relaxed benchmark constraints includes a calibration engine to execute the calibration model based on a target loss function, a weight loss function, and a budget parameter. The example apparatus further includes a calibrated weights determiner to determine calibrated weights resulting from execution of the calibration model. The example apparatus further includes a calibration model validator to incorporate a stability parameter into the calibration model in response to determining that the calibrated weights do not provide a unique solution for the executed calibration model. The stability parameter is to reduce an influence of the budget parameter on the calibration model to enable the generation of a unique solution.

Abstract: Systems and methods are disclosed for cross-system nested journey modeling based on relation of machine data. An example method includes obtaining information describing a user journey that includes multiple steps, each step corresponding to a query to be applied to events related to data sources. At least one step is a nested user journey including sub-steps. Events obtained from the data sources are related based on the obtained information. The results of the relating are displayed.

Abstract: Systems and methods for identifying one or more candidate computing entities associated with a first user of a first computing entity are disclosed. A first technical ID associated with the first computing entity and one or more parameters associated with the first computing entity are received by the ad system. A first identity fingerprint for the first computing entity is determined by the ad system. One or more candidate computing entities are identified by the ad system based on a similarity between the first identity fingerprint and an associated identity fingerprint of the one or more associated identity fingerprints of the candidate computing entity. First behavioral data is determined by the ad system based on the associated behavioral data of one or more of the one or more candidate computing entities. An advertisement based on the first behavioral data is provided by the ad system.

Abstract: Techniques for synchronization for cross-context digital item containers and collaboration are provided, receiving a user command to share a particular digital item from a first portfolio of digital items with a second portfolio of digital items. In response receiving the command to share the digital item, making a digital copy of it and placing it in the second portfolio of digital items. Subsequently, an alteration is made to the digital item and a determination is made with whom to share the alteration among those with whom the digital item had been previously shared. Those alterations can be accepted (or rejected) by the other portfolios. When they are accepted, they are applied to the digital copy.

Abstract: A method and system for modeling cyber-security events are provided. The method includes receiving a plurality of cyber-security events, wherein each of the plurality of the cyber-security events defines at least one entity; for each of the plurality of received cyber-security events, processing a received cyber-security event to identify at least one key-value; mapping the at least one identified key-value to at least one data field; modeling the received cyber-security event to a security model, wherein the security model defines a specific activity related to the at least one entity, wherein the modeling is based on at least one modeling rule and the at least one identified key-value; and generating a graph based on the security model.

Abstract: Systems, devices, methods, media, and instructions for automated image processing and content curation are described. In one embodiment a server computer system communicates at least a portion of a first content collection to a first client device, and receives a first selection communication in response, the first selection communication identifying a first piece of content of the first plurality of pieces of content. The server analyzes analyzing the first piece of content to identify a set of context values for the first piece of content, and accesses accessing a second content collection comprising pieces of content sharing at least a portion of the set of context values of the first piece of content. In various embodiments, different content values, image processing operations, and content selection operations are used to curate the content collections.

Abstract: The present disclosure may provide a stand-alone application, API, or SDK, configured to, for example, but not be limited to: i) register digital assets, physical assets, virtual assets, brand assets, media assets, and mobile assets associated with a platform user; ii) associate content to be delivered in response to an activation of those assets, including interactivity criteria, if applicable; iii) specify triggers for delivering the content and target consumer profiles for receiving the content; and iv) transmit content for engaging the consumer at the right time and/or place, with the targeted profile, and v) track user engagement and provide analytics on consumer engagement.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media that dynamically modify content distribution campaigns based on triggering conditions and actions. In particular, systems described herein can provide a user interface for display to a publisher device that includes a plurality of selectable options for setting triggering conditions and/or actions. For example, the disclosed systems can utilize a machine learning model to generate suggested triggering conditions and/or actions for one or more content distribution campaigns of a provider. Moreover, the disclosed systems can generate custom rules based on selected triggering conditions and actions and apply the custom rules during execution of digital content campaigns. For instance, the disclosed systems can monitor performance of content campaigns, detect triggering conditions, and dynamically modify digital content campaigns based on actions corresponding to the triggering conditions.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein are directed to a Message Diet Engine that generates a pool of messages for a plurality member accounts of a social network service. Each message being of a respective message type from a plurality of message types and targeted to a specific member account. For each respective member account, the Message Diet Engine selects a minimum number of messages, from the pool of messages, targeted to the respective member account that prompts an expected social network activity target and avoids an expected number of complaints. Based on the selected minimum number of messages for each respective member account, the Message Diet Engine identifies a total minimum number of messages, from the pool of messages, to be sent to the plurality of member accounts that prompts an expected total social network activity target and avoids a total expected number of complaints.

Abstract: The present invention provides techniques for use in association with online advertising, relating to use of serving thresholds, associated with predicted click through rates, and delivery policies, associated with advertising inventory serving and distribution. An offline-trained machine learning-based model may be utilized in advertising serving decision-making in connection with serving opportunities. However, serving thresholds and delivery policies, for use in association with the model in serving decision-making, may be adjusted online, such as in real-time or near real-time, based on information obtained online affecting factors such as predicted click through rates and advertising inventory distribution.

Abstract: An update basis for updating digital content in a digital medium environment is described. The digital content is updated by incorporating new digital content components from a service provider system, such as a stock content service, to keep the digital content from seeming stale to client device users. The service provider system controls provision of digital content components according to an update basis described in a component request. In part, component requests ask that the service provider system provide digital content components for incorporation with digital content. Component requests also describe a timing basis with which digital content components are to be provided as updates. By way of example, the timing basis may correspond to a time interval (e.g., daily, weekly, monthly, seasonally, times of day, and so on), receiving user input in relation to the digital content (e.g., a navigation input to a web page), and so forth.

Abstract: Techniques for distributing online ads by targeting online ad requests using test data to predict performance. The techniques can target ad requests in automated online advertising systems in which ad requests are generated by an ad exchange server and bids are placed by marketer devices in real time. The techniques aggregate bid units and compare bid unit characteristics to select bid units to target in ways that address data sparsity, variance, and volume issues. Data sparsity issues are addressed by aggregating bid units to avoid using bid units having insufficient data. Data variance issues are addressed by computing stability metrics for bid units that enable discounting the effect of outliers. Data volume and processing efficiency issues are addressed by grouping similar bid units based on similar metrics (e.g., normalized ROI) and/or similar stability scores, and then ranking the bid units and selecting the top ranked bid units to target.

Abstract: This disclosure relates to systems and methods that include configuring a machine learning system to train on a plurality of messages, the machine learning system to output an expected number of positive responses and an expected number of negative responses based on an input message, determining a threshold differential and a weight value using responses to the plurality of messages, and sending the input message in response to a differential between the expected number of positive responses and the weight multiplied by the expected number of negative responses being above the threshold differential.

Abstract: To implement a multi-touch attribution model, a conversion event resulting from user activity is programmatically detected. A set of events that precede the conversion event is identified. Respective events of the set occur on respective websites. The conversion event is attributed to multiple websites of the respective websites.

Abstract: A system, method, and apparatus are provided for propagating a status among related events. A relationship component of the system maintains a graph of the related events and, upon assignment of a status to an event identifies one or more related events (e.g., the root event, other ancestor events, descendant events). A retention component of the system includes multiple nodes that maintain user records (e.g., sharded by user identifier) storing events associated with the members and that also maintain separate event status tables to identify statuses of selected events. For example, an event status table may store statuses of root events and/or other ancestor events from which a given subsequent event may inherit or derive a status. An event status may reflect a quality or characteristic of the event (e.g., spam, low quality, language of the event), a status of the associated user (e.g., fame, level of influence), etc.

Abstract: Methods and systems are provided for providing suggested edits for content placed into a webpage under construction using a webpage content recommendation system. Attributes associated with placed content added to a webpage under construction can be compared with predictive content to determine if any edits are predicted to increase effectives of the webpage. Predictive content can be content that is the same, or similar to, the placed content added to the webpage. Predictive content can be taken from a webpage in the same category as the webpage (e.g., a category can be vertical sporting goods stores or healthcare providers) or from deployed pages on the same website as the webpage. In this way, a suggested edit can be determined based on the predictive content and provided to a user.

Abstract: Techniques are provided for dynamically generating content. A request for content about a first entity is received from a client device. In response to receiving the request, an identity of a second entity of the client device is determined. Based on the identity, attributes of the second entity are identified. It is determined whether the attributes satisfy targeting criteria of a campaign that was initiated by the first entity. In response to determining that the attributes satisfy the targeting criteria, a first number of entities that (i) share one or more attributes in common with the second entity and (ii) satisfy the targeting criteria is determined. Also, a second number of entities that share the one or more attributes in common with the second entity is determined. A ratio is calculated based on the two numbers. First content that specifies the ratio is sent to the client device for display.

Abstract: Supplemental content can be determined through a server-side process, wherein a primary content provider can obtain the supplemental content from a supplemental content provider before any of the content is sent to the client device initially requesting the primary content. A primary content provider submits a request that can include an authorization token for the primary content provider, a publisher token including a proxy identifier for the user, application, or client device, and other relevant information. The supplemental content provider can verify the information and select targeted content based on the information. The supplemental content can then be provided to the primary content provider for incorporation with the primary content. The primary content provider can adjust the layout or selection before sending to the client device for display.

Abstract: Systems and methods are provided for optimizing campaigns (such as marketing campaigns) based on both short term and long term behaviors of users. A computing system learns an incremental outcome prediction model using training data comprising a marketing campaign log entry of a subject user and another marketing campaign log entry of a corresponding user, which represents a counterfactual outcome for the subject user. A marketing campaign can be selected for another user using the learned model.

Abstract: Introduced here are communication optimization platforms configured to improve comprehension, persuasion, or clarity of communications. Initially, a communication optimization platform can acquire input sample(s) that are associated with a source audience. The communication optimization platform can then create a linguistic profile for the source audience by examining the content of the input sample(s). Additionally or alternatively, the communication optimization platform may produce a psychographic profile that specifies various characteristics of the source audience, such as personality, opinions, attitudes, interests, etc. The communication optimization platform can then generate, based on the linguistic profile and/or the psychographic profile, affinity language for communicating with a target audience. By incorporating the affinity language into communications, the communication optimization platform can increase appeal to the target audience.

Abstract: A computer-implemented method for generating creative type suggestions for an online content provider is provided. The method uses a computing device including a processor and a memory. The method includes training a first model with historical information including one or more of (i) serving performance of online advertisements and (ii) advertiser information. The method also includes computing a preliminary creative type suggestion using at least the first model. The method further includes modifying the preliminary creative type suggestion based at least in part on past suggestion performance to generate a final creative type suggestion. The method also includes presenting the final creative type suggestion to the online content provider.

Abstract: A method for stimulating neural activity in the brain of a user of an apparatus with a display screen by causing at least one portion of the display screen to flicker in a controlled manner and utilizing the apparatus to measure an effect on a user exposed to the flicker for a time.

Abstract: A system and method for performing cross-platform data analytics of advertising campaign information.

Abstract: Apparatus, systems, articles of manufacture, and methods are disclosed for correcting systematic tuning defects. An example apparatus includes a defect analyzer to identify a suspect time window in tuning volume data of return path data reported by set top boxes. The example apparatus further includes a return path data transformer to identify a first return path data entry indicating a first set top box reported a first transition to an off state at a first time during the suspect time window and to modify the first return path data entry to (1) eliminate the first transition to the off state at the first time and (2) assign the first return path data entry a first duration to remain in an on state after the first time, where the first duration is determined based on monitoring data reported from media device meters monitoring media presentation devices.

Abstract: The disclosure is directed to a system, method, and computer program product for detecting and responding to changes in the performance of an ad. In a first phase, an expected performance value for an ad is calculated. In a second phase, the performance of the ad is monitored in intervals, wherein for each interval, the response rate of the ad during the interval is calculated and compared to the expected performance value, an upper performance limit, and a lower performance limit. The ad is replaced or the expected performance value is recalculated, depending on how the response rate compares to the expected performance value, the upper performance limit, and the lower performance limit.

Abstract: An online system determines how presenting an awareness campaign to a user will affect the user's likelihood of converting to a related direct response campaign. For the user, the online system creates a benchmark exposure profile representing the user's exposure history before the awareness campaign. Similarly, the online system determines the user's simulated exposure profile, which represents the user's brand exposure history after having been exposed to the awareness campaign. A response prediction for the direct response campaign is determined for the benchmark exposure profile and the simulated exposure profile. The online system estimates the difference between the response prediction and the simulated response prediction to determine a delivery control value of presenting the awareness campaign to a user. The delivery control value is used to determine an effective impression value for the awareness campaign and conversion value for the related direct response campaign.

Abstract: A method, apparatus, and computer program product are disclosed to improve generation of electronic communications. The method may provide a plurality of content slots each configured to receive content, the content comprising at least one of promotion content or non-promotion content. The method may also include maintaining a database comprising a plurality of promotion content generators and non-promotion content generators, and determining, using a processor, one of the plurality of promotion content generators or non-promotion content generators for respectively supplying corresponding promotion content or non-promotion content to each of the plurality of content slots. The determining the one of the plurality of promotion content generators or non-promotion content generators may include determining selection parameters, and scoring the plurality of promotion content generators and non-promotion content generators based at least in part on the selection parameters.

Abstract: A system includes a field-specific model; a log analysis engine; a drill analysis engine; an interface; and computational circuitry in communication with the field-specific model, the log analysis engine, the drill analysis engine, and the interface. The computational circuitry is to: prescribe a drill recipe using the drill analysis engine based on the field-specific model, the drill recipe identifying prescribed segments, mud flow parameters, and drill parameters, each prescribed segment of the prescribed segments including an associated depth; receive a drill log in narrative text format via the interface; detect a drill event inconsistent with the drill recipe by analyzing the drill log with the log analysis engine; and prescribe an adjusted drill recipe using the drill analysis engine based on the field-specific model in response to the drill event, the adjusted drill recipe including adjusted prescribed segments.