Abstract: Techniques for implementing artificial crowd intelligence via networking of recommendation engines are disclosed. In some example embodiments, a base recommendation engine performs a computer-implemented method comprising: receiving a recommendation request; generating a first plurality of recommendations based on the recommendation request using a base recommendation model; obtaining one or more other recommendations from one or more other recommendation engines, each one of the other recommendation engines being configured to generate the other recommendations based on the recommendation request using a corresponding recommendation model; obtaining a corresponding weight for the other recommendation engine(s); selecting at least one recommendation from the first plurality of recommendations and the other recommendation(s) using the corresponding weight(s); and causing the selected recommendation(s) to be displayed.

Abstract: A data-brokerage service that facilitates data sharing between Internet-of-Things (IoT) platforms via peer-to-peer connections is described. In various embodiments, the data-brokerage service receives, from an IoT platform acting as data consumer, a selection of data fields included in a plurality of data streams provided from a plurality of respective IoT platforms acting as data producers. Responsive to the selection, the data-brokerage service causes the plurality of data-producer platforms to stream at least the selected data fields of the plurality of data streams to the data-consumer platform, and causes the data-consumer platform to combine the streamed data fields received from the plurality of data-producer platforms into a single target data stream.

Abstract: According to some embodiments, a security model data store may contain a plurality of potential security policies, each accessible by multiple external applications. A security specifications data store may contain a plurality of potential security specifications, each accessible by the multiple external applications. A security policy engine computer platform may receive from an external application an indication identifying a security policy package. The security policy engine may then retrieve, based on the received indication, one of the potential security models from the security policy data store. Similarly, the security policy engine may retrieve, based on the received indication, one of the potential security specifications from the security specifications data store.

Abstract: System and methods for enforcing service level agreements (SLAs) between computing platforms engaged in (e.g., Internet-of-Things) data exchange via peer-to-peer (P2P) connections are described. In accordance with various embodiments, data traffic via the P2P connections is monitored, and if an SLA violation is detected, data streams are rerouted to cure the violation.

Abstract: Techniques for implementing artificial crowd intelligence via networking of recommendation engines are disclosed. In some example embodiments, a base recommendation engine performs a computer-implemented method comprising: receiving a recommendation request; generating a first plurality of recommendations based on the recommendation request using a base recommendation model; obtaining one or more other recommendations from one or more other recommendation engines, each one of the other recommendation engines being configured to generate the other recommendations based on the recommendation request using a corresponding recommendation model; obtaining a corresponding weight for the other recommendation engine(s); selecting at least one recommendation from the first plurality of recommendations and the other recommendation(s) using the corresponding weight(s); and causing the selected recommendation(s) to be displayed.

Abstract: System and methods for enforcing service level agreements (SLAs) between computing platforms engaged in (e.g., Internet-of-Things) data exchange via peer-to-peer (P2P) connections are described. In accordance with various embodiments, data traffic via the P2P connections is monitored, and if an SLA violation is detected, data streams are rerouted to cure the violation.

Abstract: A service descriptor file is retrieved from a remote database by a server, where the service descriptor file describes a service corresponding to a service-specific chatbot requested by a user. The received service descriptor is parsed to obtain a capability and relevant service data associated with the service. The service-specific chatbot is generated with at least one object that is based on the obtained capability and relevant service data, where the at least one object includes intents, expressions, and skills that correspond to the service. The generated service-specific chatbot is provided to the user through at least one channel to enable an interaction with the service-specific chatbot with a graphical user interface.

Abstract: The present disclosure involves systems, software, and computer implemented methods for accessing an object store. One example method includes providing a persistency factory object configured to provide access to multiple types of persistency adapters. Each type of persistency adapter is configured to interface with a particular object store. A persistency adapter request is received from a consumer. A type of adapter to provide is determined. A determination is made that the consumer is configured to interface with a first object store and that a first persistency adapter class is associated with the first object store. A run-time reference to an instance of the first persistency adapter class is provided to the consumer. A first object store operation request to perform a first object store operation is received. The instance of the first persistency adapter class interfaces with the first object store to fulfill the first object store operation request.

Abstract: A rule is received at a client application from an input text control. The received rule includes a sequence of characters and is parsed into a plurality of tokens. For each of the tokens, a plurality of behaviors associated with that token are configured to generate a behavior configuration. Each of the generated behavior configurations can be modified by an authorized user. A user interface (UI) control is generated based on the behavior configurations.

Abstract: At each delegate device and each non-delegate device of a logical device hierarchy, a data cube is generated. The logical device hierarchy includes more than one level, and each level includes one or more groups, and each group includes one delegate device and one or more non-delegate devices. At each delegate device, data cubes are received from the one or more non-delegate devices associated with the same group. At each delegate device, data cubes are received from delegate devices of a different group, and that delegate device is the parent of the delegate devices associated with a different group. At each delegate device, the received data cubes are aggregated into a weighted data cube. From each delegate device, the weighted data cube are outputted to the parent of the delegate device.

Abstract: Input data is received, by a server, for a user from one or more data sources. A set of user language features associated with the input data are determined. The set of user language features is compared to multiple sets of known language features. Each set of known language features includes language features associated with the use of a non-native language by a speaker of a respective native language. A native language of the user is determined based on the comparing. A personalized recommendation is generated based on the determined native language of the user.

Abstract: A data-brokerage service that facilitates data sharing between Internet-of-Things (IoT) platforms via peer-to-peer connections is described. In various embodiments, the data-brokerage service receives, from an IoT platform acting as data consumer, a selection of data fields included in a plurality of data streams provided from a plurality of respective IoT platforms acting as data producers. Responsive to the selection, the data-brokerage service causes the plurality of data-producer platforms to stream at least the selected data fields of the plurality of data streams to the data-consumer platform, and causes the data-consumer platform to combine the streamed data fields received from the plurality of data-producer platforms into a single target data stream.

Abstract: The present disclosure involves systems, software, and computer implemented methods for remotely executing binaries in a containerized computing environment using a lightweight inter-process communications protocol (IPC) and UNIX domain sockets. One example method includes establishing, in a shared computing image comprising a plurality of containers, a listening UNIX domain socket, where the listening UNIX domain socket is shared between all containers in the shared computing image. A request to execute a binary in the target container is received at a target container and from a client container using the listening UNIX domain socket. A worker service is generated in the target container. The worker service executes the binary in the target container. A return exit code associated with the executed binary is received and sent to the client container using the UNIX domain socket.

Abstract: Disclosed herein are system, method, and computer program product embodiments for generating an overview panel that includes content received from data sources. An embodiment operates by a computer implemented method that includes determining the user, the user's role, and/or domains associated with the user in order to determine the content and/or data sources from which content should be received. The method further includes parsing the content from the data sources associated with the user, the user's role, and/or domains and generating cards to display the content from the data sources in a unified and cohesive manner.

Abstract: The disclosure generally describes methods, software, and systems, including a method for providing a recommended action. Data that is associated with requests and that is used in supporting actions made regarding the requests is collected from multiple sources. Default criteria based on the data and supporting a determination of a recommended action responsive to the given request is provided for presentation in the user interface. The user interface includes interactive sliders, each interactive slider being associated with a criterion and having a default slider position associated with a relative weighting factor for the criterion. An algorithm is executed that is associated with a request type of the given request. Absolute weights are assigned to the default criteria using the relative weighting factors. The given request is evaluated using the default criteria and the absolute weights to determine the recommended action, which is provided for presentation in the user interface.

Abstract: First resource utilization information for a first customer of a cloud platform and second resource utilization information for a second customer of the cloud platform are accessed. A first prediction regarding future resource utilization by the first customer and a second prediction regarding future resource utilization by the second customer are determined. A resource reallocation recommendation that recommends reallocating one or more resources between the first customer and the second customer is determined, based on the first prediction and the second prediction. The resource reallocation recommendation is provided.

Abstract: Various embodiments of systems, computer program products, and methods to provide a static analysis rules repository and a training data repository are described herein. In an aspect, a list of commit metadata associated with historical source code are retrieved from one or more repositories. Commits associated with the list of commit metadata are filtered based on commit types. Further, the filtered commits are analyzed to score the commits based on usage of the commits. Based on scoring, the static analysis rules repository including one or more new rules for the static code analysis and the training data repository including source code examples for the software source coding are provided.

Abstract: Implementations of the present disclosure disclose synchronizing UI controls. At each user interface (UI) control associated with an application, a corresponding plugin is created, where the created plugin is associated with a technology and a UI view, and where the application includes a plurality of UI controls. Each UI control associated with the application is registered to a database, where each UI control is registered as a subscriber associated with a tag. An event is sent from at least one UI control to the database according to a change that occurred on that UI control. Each of the registered UI controls associated with the tag are updated.

Abstract: A command is received in a cloud-computing environment from an integrated development environment (IDE), where the command is to update runtime software application content in an application container associated with the runtime software application content, and where the command contains new software application content. Without terminating the application container, a connection is opened to the application container using the application container name as an identifier, and at least some of the runtime software application content in the application container is modified using the new software application content.

Abstract: At each delegate device and each non-delegate device of a logical device hierarchy, a data cube is generated. The logical device hierarchy includes more than one level, and each level includes one or more groups, and each group includes one delegate device and one or more non-delegate devices. At each delegate device, data cubes are received from the one or more non-delegate devices associated with the same group. At each delegate device, data cubes are received from delegate devices of a different group, and that delegate device is the parent of the delegate devices associated with a different group. At each delegate device, the received data cubes are aggregated into a weighted data cube. From each delegate device, the weighted data cube are outputted to the parent of the delegate device.