Abstract:
A processing system including at least one processor may obtain a first request for delivery of a first data set to a first destination, map the first request to a first information model, obtain a second request for delivery of a second data set to a second destination, map the second request to a second information model, and identify that a portion of data is part of both data sets. The processing system may next determine a plan for configuring data pipeline components for delivering the first data set to the first destination and the second data set to the second destination, the plan comprising: a combination of the first information model and the second information model, and at least one modification to the combination. The processing system may then configure the data pipeline components in accordance with the plan.
Abstract:
A processing system including at least one processor may obtain a first request for delivery of a first data set to a first destination, map the first request to a first information model, obtain a second request for delivery of a second data set to a second destination, map the second request to a second information model, and identify that a portion of data is part of both data sets. The processing system may next determine a plan for configuring data pipeline components for delivering the first data set to the first destination and the second data set to the second destination, the plan comprising: a combination of the first information model and the second information model, and at least one modification to the combination. The processing system may then configure the data pipeline components in accordance with the plan.
Abstract:
Concepts and technologies disclosed herein are directed to automated control loop searching (“ACLS”). According to one aspect disclosed herein, an ACLS system can create a search model that provides high-level information regarding what the ACLS system should search for when a search pattern is detected within data that is output from execution of a control loop. The ACLS system can activate a control loop system that executes the control loop to yield the data as output. The ACLS system can detect the search pattern within data, and in response, the ACLS system can execute, based upon the search model, a search of the data. The ACLS system can collect search results of the search and select additional data from the search results.
Abstract:
Concepts and technologies disclosed herein are directed to automated control loop grading and data labeling (“ACLGDL”). An ACLGDL system analyzes results of an execution, by a control loop system, of a control loop. The ACLGDL system can grade the results. The ACLGDL system also can instruct, based at least in part upon the grade of the results of the execution, the control loop system to collect additional data. The ACLGDL system can label the additional data for use by an output system. The ACLGDL system can establish plurality of policies including a grading-analysis policy, a grading-results policy, a labeling-collection policy, a labeling policy, a publishing policy, and a notification policy. The ACLGDL system can publish the data labeled in accordance with the labeling policy based, at least in part, upon the publishing policy. The ACLGDL system can notify the output system based, at least in part, upon the notification policy.
Abstract:
A processing system including at least one processor may obtain a first request for delivery of a first data set to a first destination, map the first request to a first information model, obtain a second request for delivery of a second data set to a second destination, map the second request to a second information model, and identify that a portion of data is part of both data sets. The processing system may next determine a plan for configuring data pipeline components for delivering the first data set to the first destination and the second data set to the second destination, the plan comprising: a combination of the first information model and the second information model, and at least one modification to the combination. The processing system may then configure the data pipeline components in accordance with the plan.
Abstract:
A method for managing appointments using a wireless device includes receiving scheduling data for a future appointment including a time associated with the future appointment. A current location of the wireless device is determined, and a reminder for the future appointment is provided at a time prior to the future appointment based on the current location of the wireless device. Fox example, the reminder may be provided at a time that varies based on the current location of the wireless device, a location associated with the future appointment, and an estimated travel time between the current location of the device and the location associated with the future appointment. Related methods, devices, and computer program products are also discussed.
Abstract:
Automatic rating optimization is described. In an embodiment, ratings of a program can be received from one or more rating sources. Based on these ratings, a representation of a content selection mechanism can be sent to potential consumers of the content. Access events for the content can be counted over a duration of time so a determination can be made regarding how the ratings provided by each of the rating sources affect popularity of the content. A weight accorded to ratings received from each of the rating sources can be adjusted based on the determination. Profiles can be established for consumers and/or rating sources.
Abstract:
Methods, systems, and computer program products that automatically control the installation of software applications on a device are provided. The installation of a software application on a device is detected. The installation is temporarily halted and information about the detected software application installation is collected. A danger level of the detected software application is assessed based upon the collected information. Installation of the detected software application is allowed to continue if the assessed danger level is below a threshold level and installation of the detected software application is terminated if the assessed danger level is above the threshold level.