Abstract: A real-time messaging platform allows advertiser accounts to pay to insert candidate messages into the message streams requested by account holders. To accommodate multiple advertisers, the messaging platform controls an auction process that determines which candidate messages are selected for inclusion in a requested account holder's message stream. Selection is based on a bid for the candidate message, the message stream that is requested, and a variety of other factors that vary depending upon the implementation. The process for selection of candidate messages generally includes the following steps, though any given step may be omitted or combined into another step in a different implementation: targeting, filtering, prediction, ranking, and selection.

Abstract: Conversations can be generated automatically based on any given persona. The conversations can be produced by a language generation model that automatically generates persona-based language in response to a message, wherein a persona identifies a type of person with role specific characteristics. After a language generation model is acquired, for example by identifying a predefined model or generating a new model, the language generation model can be provisioned for use by a conversational agent, such as a chatbot, to enhance the functionality of the conversational agent.

Abstract: A real-time messaging platform allows advertiser accounts to pay to insert candidate messages into the message streams requested by account holders. To accommodate multiple advertisers, the messaging platform controls an auction process that determines which candidate messages are selected for inclusion in a requested account holder's message stream. Selection is based on a bid for the candidate message, the message stream that is requested, and a variety of other factors that vary depending upon the implementation. The process for selection of candidate messages generally includes the following steps, though any given step may be omitted or combined into another step in a different implementation: targeting, filtering, prediction, ranking, and selection.

Abstract: An example system includes a memory store of aggregate definitions. Each aggregate definition specifies a key value, an output store, a feature, a half-life value, and an aggregate operation metric to apply to a cross of the feature and the half-life value to generate aggregate metrics. The system also includes an aggregation engine that generates aggregate feature records from the input source based on the aggregate definitions and stores the aggregate feature records in the output store. An aggregate feature record includes an aggregate of the metric for the feature decayed over time using the half-life. The system also includes a query service that identifies, using the aggregate definitions, responsive aggregate feature records that satisfy parameters of a received request, applies the half-life to the responsive feature records, and provides the responsive feature records to a requester, the requester using the responsive feature records as input for a neural network.

Abstract: A real-time messaging platform allows advertiser accounts to pay to insert candidate messages into the message streams requested by account holders. To accommodate multiple advertisers, the messaging platform controls an auction process that determines which candidate messages are selected for inclusion in a requested account holder's message stream. Selection is based on a bid for the candidate message, the message stream that is requested, and a variety of other factors that vary depending upon the implementation. The process for selection of candidate messages generally includes the following steps, though any given step may be omitted or combined into another step in a different implementation: targeting, filtering, prediction, ranking, and selection.

Abstract: A real-time messaging platform allows advertiser accounts to pay to insert candidate messages into the message streams requested by account holders. To accommodate multiple advertisers, the messaging platform controls an auction process that determines which candidate messages are selected for inclusion in a requested account holder's message stream. Selection is based on a bid for the candidate message, the message stream that is requested, and a variety of other factors that vary depending upon the implementation. The process for selection of candidate messages generally includes the following steps, though any given step may be omitted or combined into another step in a different implementation: targeting, filtering, prediction, ranking, and selection.

Abstract: A real-time messaging platform allows advertiser accounts to pay to insert candidate messages into the message streams requested by account holders. To accommodate multiple advertisers, the messaging platform controls an auction process that determines which candidate messages are selected for inclusion in a requested account holder's message stream. Selection is based on a bid for the candidate message, the message stream that is requested, and a variety of other factors that vary depending upon the implementation. The process for selection of candidate messages generally includes the following steps, though any given step may be omitted or combined into another step in a different implementation: targeting, filtering, prediction, ranking, and selection.

Abstract: The claimed subject matter provides a method and a system for the efficient indexing of error tolerant set containment. An exemplary method comprises obtaining a frequency threshold and a query set. All tokens or token sets within the query set are determined, and then all minimal infrequent tokens or all minimal infrequent tokens sets of data records are found and used to build an index. The minimal infrequent tokens or minimal infrequent tokensets are processed in a fixed order, and then a collection of signatures for each minimal infrequent token or token set is determined.

Abstract: The claimed subject matter provides a method and a system for the efficient indexing of error tolerant set containment. An exemplary method comprises obtaining a frequency threshold and a query set. All tokens or token sets within the query set are determined, and then all minimal infrequent tokens or all minimal infrequent tokens sets of data records are found and used to build an index. The minimal infrequent tokens or minimal infrequent tokensets are processed in a fixed order, and then a collection of signatures for each minimal infrequent token or token set is determined.

Abstract: A system of query scheduling to maximize work sharing. The system schedules queries to account for future queries possessing a sharability component. Included in the system are operations for assigning an incoming query to a query queue based on a sharability characteristic of the incoming query, and evaluating a priority function for each member of a plurality of query queues to identify one highest priority query queue. The priority function accounts for the probability that a future incoming query will contain the sharability characteristic common to a member of the plurality of query queues. The system of query scheduling to maximize work sharing selects a batch of queries from the highest priority query queue, and dispatches the batch to one or more query execution units.

Abstract: A system of query scheduling to maximize work sharing. The system schedules queries to account for future queries possessing a sharability component. Included in the system are operations for assigning an incoming query to a query queue based on a sharability characteristic of the incoming query, and evaluating a priority function for each member of a plurality of query queues to identify one highest priority query queue. The priority function accounts for the probability that a future incoming query will contain the sharability characteristic common to a member of the plurality of query queues. The system of query scheduling to maximize work sharing selects a batch of queries from the highest priority query queue, and dispatches the batch to one or more query execution units.

Abstract: An improved system and method for asynchronous update of indexes in a distributed database is provided. A database server may receive the request to update the data and may update the data in a primary data table of the distributed database. An asynchronous index update of the indexes may be initiated at the time a record is updated in a data table and then control may be returned to a client to perform another data update. An activity cache may be provided for caching the records updated by a client so that when the client requests a subsequent read, the updated records may be available in the activity cache to support the various guarantees for reading the data. Advantageously, the asynchronous index update scheme may provide increased performance and more scalability while efficiently maintaining indexes over database tables in a large scale, replicated, distributed database.

Abstract: A system and method provide adaptive frequency scaling for predicting the load on a processing unit and dynamically changing its clock frequency while keeping the synchronization with other processing units. The amount of data in an input memory waiting to be processed is a good indicator of the current load and thus embodiments of the present invention utilize the same concept for predicting the load on the processing unit. The frequency of operation is thus changed on the basis of the percentage of memory being occupied by its input data. Algorithms according to embodiments of the present invention allow the processing unit to use the maximum possible clock frequency only when it is required and to run at some lower frequencies in low processing power requirements. Operating the circuit at low frequency helps in reducing power consumption.