Abstract: Machine learning (ML) is provided at edge computing devices based on distributed feedback received from the edge computing devices. A trained instance of an ML model is received at the edge computing devices via communications networks from an ML model manager. Feedback data including labeled observations is generated by the execution of the trained instance of the ML model at the edge computing devices on unlabeled observations captured by the edge computing devices. The feedback data is transmitted from the edge computing devices to a machine learning model manager. A re-trained instance of the machine learning model is generated from the trained instance using the collected feedback data. The re-trained instance of the machine learning model is received at the edge computing devices from the machine learning model manager. The re-trained instance of the machine learning model is executed at the edge computing devices.

Abstract: Intelligent learning and management of networked architectures is disclosed. A network architecture can be mapped to identify a set of interconnected hardware and software elements that comprise the network architecture. Data sources associated with the set of interconnected hardware and software elements can be identified and employed to compile data associated with the elements. The data can be utilized to determine an action to address potential negative effects of a change to the network architecture such as an update or patch. In one instance, the action corresponds to a reconfiguration of at least one of the set of interconnected hardware and software elements. Further, machine learning can be employed to determine a particular configuration. Once determined the action can be implemented on the network architecture.

Abstract: A server can include a detection module for monitoring an electronic account and detecting irregular or fraudulent activities. The detection module can be a machine learning model configured to detect activities or patterns indicative of an account being compromised, hacked or accessed by unauthorized users. Upon detection of the irregular activities or patterns, the detection module can transmit a notification or signal to a trigger module which can implement remedial actions. The trigger module can receive the signal from the detection module and execute an action in accordance with a trigger plan. The trigger plan can include various information and a range of actions, which can be selected and/or executed based on the information included in the signal.

Abstract: The present description is directed towards systems and methods for directing a user request for content over a network to a given content server on the basis of one or more rules. Methods and systems implemented in accordance with the present description comprise receiving a request for content form a user, the request for content including a profile of the user identifying one or more characteristics associated with the user. One or more rules are retrieved for identifying a content server to which a request for content is to be delivered, the one or more rules including at least one of business rules, network rules, and user profile rules. The one or more retrieved rules are applied to the request for content to identify a content server to which the request for content is to be delivered and the request for content is delivered to the identified content server.

Abstract: The present invention extends to methods, systems, and computer program products for automating DevOps toolchains. A user registers with a platform provider through a user interface that provides a unified self-service portal. Subsequently, the user can login to a platform configuration system to access a user landing page and/or dashboard. The user can select DevOps platform tools to be installed and enter configuration information. When the user is satisfied with selected DevOps platform tools and entered configuration, the user can select a “confirm” user-interface control (e.g., a button). In response, the selected DevOps tools are installed (with a relatively high level of automation) as DevOps platform. The user can also change DevOps platforms through the user interface (also with a relatively high level of automation), including migrating, deleting, and upgrading DevOps tools.

Abstract: Disclosed herein are methods and systems for facilitating information and expertise distribution via a communication network. A method at a first computing device may include receiving a request for information from a second computing device, determining at least one third computing device based on an analysis of the request for information, communicating the request for information to the determined at least one third computing device, receiving a response corresponding to the request for information from the determined at least one third computing device, adjusting a credit level of a user associated with the determined at least one third computing device based on the received response, and communicating the response to the second computing device. The credit level of the user may indicate one or more credits earned by the user.

Abstract: Systems and methods for ticket-based provisioning of cloud infrastructure from one or more cloud providers to build one or more computing workspaces of an enterprise. A provisioning platform provides a module catalog having one or more infrastructure-as-code (IAC) modules, each including code that is executable to provision cloud computing resources for the cloud infrastructure from the cloud providers to build the computing workspaces of the enterprise. A service catalog has one or more electronic entries mapped to and corresponding with the IAC modules of the module catalog. The service catalog receives one or more tickets that each specify at least one of the electronic entries in the service catalog, to bind each specified electronic entry with a corresponding IAC module, causing the provisioning platform to instantiate on the more cloud providers the computing resources for the cloud infrastructure corresponding to the ticket.

Abstract: Systems and methods accessing remote digital data over a wide area network (WAN) are disclosed. In an embodiment, a network device is disclosed. The network device includes a local area network (LAN) switching fabric physical interface configured to communicate according to a LAN switching fabric protocol, a WAN physical interface configured to communicate according to a WAN protocol, and a fabric extension function configured to map LAN switching fabric interfaces to pseudo-ports, map pseudo-ports to WAN interfaces, and transmit LAN fabric datagrams received at the LAN switching fabric physical interface from the WAN physical interface via a mapped pseudo-port and a corresponding WAN interface.

Abstract: Disclosed herein are methods and systems for facilitating information and expertise distribution via a communication network. A method at a first computing device may include receiving a request for information from a second computing device, determining at least one third computing device based on an analysis of the request for information, communicating the request for information to the determined at least one third computing device, receiving a response corresponding to the request for information from the determined at least one third computing device, adjusting a credit level of a user associated with the determined at least one third computing device based on the received response, and communicating the response to the second computing device. The credit level of the user may indicate one or more credits earned by the user.

Abstract: Methods and systems automatically adjusting resources and monitoring configurations of objects of a distributed computing system in response to changes to application programs. Methods search event messages for information indicating a change in execution of an object. The information is used to determine resource allocation rules of infrastructure resources by and a monitoring configuration for the object. Expected impacts on the infrastructure resource are determined from the rules. When an expected impact is greater than an associated impact threshold, use of the infrastructure resources may be adjusted to accommodate the changes. The adjustments include scaling up or down the infrastructure resources. When the object is a virtual object, the virtual object may be migrated from one server computer to another server computer within the distributed computer system. The monitoring configuration is used to adjust tools that monitor the objects of the distributed computing system.

Abstract: Activity data of a set of tasks as a training set is obtained from a list of communication platforms associated with the tasks. For each of the tasks in the training set, a set of activity metrics is compiled according to a set of predetermined activity categories based on the activity data of each task. The activity metrics of all of the tasks in the training set are aggregated based on the activity categories to generate a data matrix. A principal component analysis is performed on the metrics of its covariance matrix to derive an activity dimension vector, where the activity dimension vector represents a distribution pattern of the activity metrics of the tasks. The activity dimension vector can be utilized to determine an activity score of a particular task, where the activity score of a task can be utilized to estimate a probability of completeness of the task.

Abstract: Described are various embodiments of methods and systems relating to impact management of IT systems, including a server-based IT management system comprising a network server having a service function object store that stores a plurality of service function objects, each service function object being a digital representation of a service function and comprising one or more service attributes and one or more service function links for linking each service function object to at least one other service function object; and a network communications interface for receiving information indicative of an operating state for each service function; wherein the operability of any given service function is determined automatically upon the reduction of operating state of any one or more other service functions based on direct and indirect linkages between the given service function and the other service functions and the respective service-loss impact values associated with each said direct and indirect linkages.

Abstract: The present disclosure relates generally to internet social media, and more specifically to techniques for determining location-related information about internet social media content. In some embodiments, a system accesses data representing a first social media post, the data including geographic location data identifying a first geographic location. The system identifies a second social media post related to the first post. The system accesses data representing the second social media post, wherein the data representing the second post does not include geographic location data identifying the first geographic location. The system analyzes the data representing the second social media post and determines a location score based at least in part on the analysis of the data representing the second social media post. If the location score exceeds a threshold location score, the system associates the second social media post with the first geographic location.

Abstract: According to certain aspects of the disclosure, a computer-implemented method computer-implemented method may be used for screening electronic communications. The method may comprise analyzing contents of an electronic communication to determine whether the contents include sensitive information. A recipient list of the electronic communication may be compared to a screening list. Based on the analyzing and the comparing, it may be determined whether the contents are permitted to be transmitted to the recipient list. Upon determining that the contents are not permitted to be transmitted to at least one party of the recipient list, a notification may be provided to an author of the electronic communication indicating that contents are not permitted to be transmitted to the at least one party of the recipient list.

Abstract: System platform, software and hardware equipment and components, and methodologies are provided for gathering, organizing, distributing and synchronizing information about events, event attendees or group activities associated with events. Event management system and methods include mobile software application platform for event participants to receive push content, and generate and share real time activity feed(s) on various social media and/or dialogue platforms via a server that transmits push information (notifications, ads, alerts, updates) to event participant's mobile application, receives activity feed information from mobile application, and selectively transmits activity feed information to social media and/or dialog platforms. Events include conferences, tradeshows, seminars, or any activities involving one or more participants. Event participants include attendees, exhibitors, speakers, sponsors, organizers, or any other groups or individuals associated with event.

Abstract: A computer-implemented method for analyzing a time-varying graph is provided. The time-varying graph includes nodes representing elements in a network, edges representing transactions between elements, and data associated with the nodes and the edges. The computer-implemented method includes constructing, using a processor, adjacency and feature matrices describing each node and edge of each time-varying graph for stacking into an adjacency tensor and describing the data of each time-varying graph for stacking into a feature tensor, respectively. The adjacency and feature tensors are partitioned into adjacency and feature training tensors and into adjacency and feature validation tensors, respectively. An embedding model and a prediction model are created using the adjacency and feature training tensors. The embedding and prediction models are validated using the adjacency and feature validation tensors to identify an optimized embedding-prediction model pair.

Abstract: Systems and methods of the present disclosure relate generally to allocation of content resources in a voice activated packet-based computer network. A request for a digital component, by a client computing device, can be fulfilled by multiple content sources. Fulfillment by the different content sources can consume different amounts of computational and network resources. The selection of the best content provider can improve the efficiency and effectiveness of data packet transmission over one or more computer networks.

Abstract: A System Solution offers a Business Entity a way to update a Native Application Client by directly downloading a new version of the Application Client from an Application Server bypassing the Application Store. A Native Application Client is updated while the current Native Application Client is running on the Client Device. A Native Application Client is divided into a Native Layer which runs directly on the Operating System of the Client Device and a Dynamic Layer that runs on the Native Layer. The System Solution automatically generates Application Clients, Application Servers, and Dashboards. The Business Entity uses the generated Dashboards to modify the Dynamic Layer by generating a new Dynamic Layer and making it available for download to the Client Device. The Navigation Parameters can be set in the Dynamic Layer allowing the Business Entity to change the application flow of the Native Application Client.

Abstract: Cloud services are often implemented as instances of applications having one or more components running on the nodes (e.g., host computers or servers) of a data center. Network services are thereby provided to a workload that uses the network resources of network interface devices (e.g., a NIC, switch, or router). The workload is a first instance of an application. The network interface devices can produce resource usage measurements of usage metrics that quantify usage of the network resources by the workload. The resource measurements can be used to produce an application network profile of the application. The application network profile can be used to select at least one of a plurality of nodes on which a second instance of the application is launched.

Abstract: A high-level functionality generates a Data Model which is used to automatically generate Applications comprising Application Clients, Application Servers, Client-Server Protocols, Dashboards and other components. These Applications are derived for different mobile and non-mobile's Operating Systems. This functionality uses Services, Service Representation, Application Flow, Rules, and Presentation Attributes. The input for the automation is a very high-level, “service” level “language,” from which all parts are automatically generated. The output of the automation also includes a way to validate the correctness of the generated Applications. The generated Dashboard provide a Business Entity with functionality to continuously update the generated Data Model based on the Services and Business Entity data, and from the updated Data Model automatically generate updated versions of the Application.