Abstract: A computer identifies, within a hierarchical database, data elements associated with a selected function associated with the database, comprising. The computer identifies at least one function associated with a hierarchical database containing data elements. The computer, in response to identifying the function, identifies within a list of indica, at least one reference indicia corresponding to the at least one function. The computer identifies within a monolithic application relevant code elements associated with the reference indicia. The computer generates an activity log associated with execution of the relevant code elements. The computer identifies, within the activity log, a group of data elements associated with the execution of the relevant code elements. The computer generates a group data element clusters using a Machine Learning algorithm. The computer identifies at least one of the group of data element clusters as relevant to the at least one function.

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 processor may identify one or more sources. The processor may identify a respective requirement of each of the one or more sources. The processor may determine if a respective requirement is different than another respective requirement. The processor may locate each of the one or more sources in a respective slice on a different container available in a server of a network.

Abstract: A model is generating for predicting energy workloads to adjust electrical energy supply to meet varying short-term energy demands at a microcosm level. A model is developed, using a computer, to facilitate predicting energy workloads for adjusting energy supplies to meet an energy demand. The model includes receiving, at the computer, input parameters of dynamic values of workloads as historical data, and generating a predictive model by analyzing the input parameters. The model further includes predicting short-term energy demands based on the predictive model, the predicted short-term energy demands include identifying a predicted peak value. Also, the model includes initiating short term energy output in an electrical grid to a transformer level component in the electrical grid based on the predicted short term energy demands.

Abstract: A method, computer program product, and a system where a processor(s) obtains a universe of social media items posted to a social media platform at a given time. The processor(s) determines a likelihood of each item of the universe of social media items becoming viral by linking each item of the universe to a breakout pattern based on predefined dimensions and bucketing each item into a defined grouping by a measure of anticipated virality of the item. The processor(s) applies a susceptible-infected-recovered (SIR) model as a differential equation to the bucketed items to determine an equilibrium and one or more breakout points. The processor(s) determines if a social media item will become viral based on whether the item matches at least one or the one or more breakout points.

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 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: 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: 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: 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: 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 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: 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 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 method, computer program product, and a system where a processor(s) obtains a universe of social media items posted to a social media platform at a given time. The processor(s) determines a likelihood of each item of the universe of social media items becoming viral by linking each item of the universe to a breakout pattern based on predefined dimensions and bucketing each item into a defined grouping by a measure of anticipated virality of the item. The processor(s) applies a susceptible-infected-recovered (SIR) model as a differential equation to the bucketed items to determine an equilibrium and one or more breakout points. The processor(s) determines if a social media item will become viral based on whether the item matches at least one or the one or more breakout points.