Abstract: A computer-implemented method includes: receiving, by a computing device, a request from a requester; determining, by the computing device, one or more delegates that are currently capable of handling the request; sending, by the computing device, a request package to each of the one or more delegates, the request package including an authentication challenge; receiving, by the computing device, a solution to the authentication challenge from a supplier, the solution being provided by a particular delegate of the one or more delegates; determining, by the computing device, the solution to the authentication challenge is valid; and instructing, by the computing device and in response to determining the solution to the authentication challenge is valid, the particular delegate to proceed with handling the request.

Abstract: A method, system, and computer program product for implementing automated software application generation is provided. The method includes scanning source code for identifying missing elements of hardware and software parameters associated with functional operation of software for development. The hardware and software parameters are analyzed and converted into configurable digital bins. An automation parameter is generated. The automation parameter is associated with portions of the software configured for automatic development and generation. Corrective actions associated with automating development of the software are generated based on the automation parameter and it is determined that the automation parameter is within a specified range of the portions. The corrective actions are executed with respect to development of the software and the software is generated.

Abstract: An approach to generating a learning path framework may be provided. A Cognitive Bot may monitor the knowledge stream of a subject matter expert (SME) to glean insights from the activities and events performed by the SME. The CogBot determine categories within the subject matter. The CogBot may tune a grade scoring engine using the insights gleaned from the knowledge stream as a threshold for the grade scoring module. The knowledge stream of a second user may be monitored by a CogBot. A grade score of the subject matter for the second user may be generated by the grade scoring engine. An expertise level associated with the categories may be determined. A learning path framework may be generated based on the generated grade score and expertise level.

Abstract: Techniques for text evaluation are provided. A curated dataset comprising a plurality of textual documents is received. A tree of classifiers is trained, based on the curated dataset, to identify use cases. A feature graph model is generated, based on the curated dataset, to determine textual similarity. A new document is received, and a plurality of requirements is extracted from the new document. For each requirement, one or more vector scores are generated by evaluating the requirement using the tree of classifiers, one or more feature scores are generated by evaluating the requirement using the feature graph model, and one or more use cases are identified for the new textual document based on the one or more vector scores and the one or more feature scores. An implementation is generated for the new document based on the one or more use cases.

Abstract: Systems and methods for analyzing machine learning of cognitive software robots (CogBots) over time are provided. In implementations, a method includes generating, by a computing device, a graph of historic learning curves based on historic learning data over time for a subject obtained from a primary cognitive software robot (CogBot) and at least one secondary CogBot; generating, by the computing device, a best probable learning curve based on the historic learning curves of the graph, wherein the best probable learning curve is predictive of future learning by the primary CogBot for the subject; and generating, by the computing device, information regarding a current status of the learning of the primary CogBot based on the best probable learning curve.

Abstract: A processor may be configured to perform operations that include computing a benefit-to-resource score for a dataset and selecting an autoencoder architecture based on the benefit-to-resource score. The autoencoder architecture may balance minimizing reconstruction loss with minimizing required storage space based on the benefit-to-resource score. The operations performed by the processor may further include transforming the dataset into transformed data with a transformation function based on the autoencoder architecture and storing the transformed data in a user space.

Abstract: An approach to generating a learning path framework may be provided. A Cognitive Bot may monitor the knowledge stream of a subject matter expert (SME) to glean insights from the activities and events performed by the SME. The CogBot determine categories within the subject matter. The CogBot may tune a grade scoring engine using the insights gleaned from the knowledge stream as a threshold for the grade scoring module. The knowledge stream of a second user may be monitored by a CogBot. A grade score of the subject matter for the second user may be generated by the grade scoring engine. An expertise level associated with the categories may be determined. A learning path framework may be generated based on the generated grade score and expertise level.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining historical data of demand response programs and demand response agreements respective to each of the users regarding a subject energy. Training dataset for a DR user pooling model includes attributes of the demand response data collected that are relevant to responsivities of the demand response programs. The DR user pooling model is trained by the training dataset by machine learning. A DR user pool is identified amongst users of the demand response program by the DR user pooling model. Users in the DR user pool respond to demands as a group and the DR user pool is adjusted to improve responsivities of the demand response programs.

Abstract: Described are techniques including a method comprising generating customer profiles in a profile datastore and selecting a subset of the customer profiles for storing in a candidate profile datastore based on qualifier constraints in a qualifier model. The method further comprises scoring the subset of the customer profiles using a scoring algorithm and determining, for each of the subset of the customer profiles, a respective preferred communication channel. The method further comprises transmitting, in an order according to a rank based on the scoring, electronic communications to a subset of the customer profiles using the respective preferred communication channels.

Abstract: Systems and methods for monitoring of utility assets using crowd-sourced digital image data are disclosed. In embodiments, a method includes: monitoring, by a computing device, incoming real-time utility data; determining, by the computing device, that a triggering event has occurred based on the monitoring; sending, by the computing device, an event message to one or more agent devices comprising a request for digital image collection at a location based on the triggering event, the event message including event information, wherein the one or more agent devices are associated with respective agents in a crowd-sourcing network; receiving, by the computing device, event data from the one or more agent devices, the event data including one or more digital images; and processing, by the computing device, the one or more digital images to determine next steps with respect to the triggering event.

Abstract: A computer implemented method is provided that includes creating an industry force graph meta model; and establishing a relationship for each maturity dimension to determine most relevant content. The most relevant content is graphed using a chromatic polynomial to map strongest industry trends in an industry force. The method continues with building traversal logic to determine most relevant technologies for the strongest industry trends in the industry force. Most relevant components of an component business model are identified, and linkages between the strongest industry trends in the industry force are made to the most relevant components of the component business model.

Abstract: A user-initiated request from a user device of a user is detected. The user-initiated request is directed to a product provider, the user-initiated request includes one or more parameters. an anonymized request is created based on the one or more parameters. The anonymized request is sent to the product provider. A provider response is received from the product provider. A targeted response is generated based on the one or more parameters of the user-initiated request and based on the provider response. The targeted response is transmitted to the user device of the user.

Abstract: Generating a work-flow diagram from technology specific literature includes using an analysis of technology specific literature which includes using natural language processing (NLP), to derive semantics for a plurality of components defined in the technology specific literature. The plurality of components are associated to symbols in a component symbol database. The associated symbols are assigned to each of the plurality of components, respectively. A relationship is determined for each of the plurality of components. Nodes are assigned, and vectors are assigned when applicable, for each of the symbols. A work-flow diagram is generated for the technology specific literature using the assigned associated symbols for each of the plurality of components and the nodes and the vectors for each of the symbols.

Abstract: A method, a computer system, and a computer program product for restoration time predictions and optimized recovery solutions is provided. Embodiments of the present invention may include selecting a dataset based on time series data. Embodiments of the present invention may include building one or more models, wherein the one or more models include a classification and regression tree model, a cross validated decision tree model or a bootstrap aggregating model. Embodiments of the present invention may include selecting a model for predictions using decision trees to reduce a variance of the model. Embodiments of the present invention may include rebuilding the model based on additional data attributes. Embodiments of the present invention may include determining an outage prioritization for each outage node. Embodiments of the present invention may include transmitting results of the outage prioritization.

Abstract: Described are techniques including a method comprising generating customer profiles in a profile datastore and selecting a subset of the customer profiles for storing in a candidate profile datastore based on qualifier constraints in a qualifier model. The method further comprises scoring the subset of the customer profiles using a scoring algorithm and determining, for each of the subset of the customer profiles, a respective preferred communication channel. The method further comprises transmitting, in an order according to a rank based on the scoring, electronic communications to a subset of the customer profiles using the respective preferred communication channels.

Abstract: A method, system, and computer program product for predicting optimal service characteristics to execute predicted IT tickets. The method may include identifying deployment characteristics for an operational system based on an architecture of the operational system. The method may also include receiving implementation data in response to past incident tickets based on the deployment characteristics. The method may also include identifying relationships within the implementation data. The method may also include predicting a volume of new tickets based on the implementation data and the relationships between the implementation data. The method may also include predicting a resolution time for high severity tickets in the volume of new tickets. The method may also include determining preferred service characteristics based on the volume of the new tickets and the resolution time for the high severity tickets.

Abstract: A method can include obtaining one or more gesture definitions. Each of the one or more gesture definitions can identify a correspondence between a set of gestures and a voice communication. The method can further include detecting that a mute function of a communication device is active. The mute function can prevent the communication device from transmitting audio data to one or more receiving devices. The method can further include obtaining gesture data from one or more input devices. The method can further include identifying a first gesture definition of the one or more gesture definitions. The identifying the first gesture definition can be based on the gesture data. The method can further include initiating a transfer of a first voice communication to the one or more receiving devices. The first voice communication can correspond to the first gesture definition.

Abstract: A computer-implemented method includes: receiving, by a computing device, a request from a requester; determining, by the computing device, one or more delegates that are currently capable of handling the request; sending, by the computing device, a request package to each of the one or more delegates, the request package including an authentication challenge; receiving, by the computing device, a solution to the authentication challenge from a supplier, the solution being provided by a particular delegate of the one or more delegates; determining, by the computing device, the solution to the authentication challenge is valid; and instructing, by the computing device and in response to determining the solution to the authentication challenge is valid, the particular delegate to proceed with handling the request.

Abstract: A system and method for managing the provisioning of electricity to an electric vehicle includes identifying an electric vehicle when the electric vehicle connects to a charging point; determining whether the electric vehicle is associated with a smart contract; validating the smart contract associated with the electric vehicle; creating a charging transaction for charging the electric vehicle; and applying the smart contract associated with the electric vehicle against the charging transaction. The electric vehicle electricity contract management system and method may use a consensus system such as a distributed ledger system or blockchain.

Abstract: A computer system message generated by an application programming interface (API) or addressed to the API can be received. A first data sensitivity score for at least a first of a plurality of data elements in a payload of the computer system message and at least second data sensitivity score for at least a second of the plurality of data elements in the payload of the computer system message can be determined. Based on the first data sensitivity score and at least the second data sensitivity score, a differential security can be applied to the computer system message. Applying the differential security can include masking the first of the plurality of data elements and not masking the second of the plurality of data elements. The computer system message can be electronically communicated the to a destination to which the message is addressed.