Abstract: A method, computer system, and a computer program product for generating a conversational bot for an application programming interface (API)is provided. The present invention may include parsing an API schema. The present invention may include generating sentences for the conversational bot from the parsed API schema. The present invention may include constructing the conversational bot by training a deep learning model. The present invention may include receiving a natural language expression from a user. The present invention may include determining whether the natural language expression is enough to activate the bot.

Abstract: A query can be received from a user. The query can be sent to a plurality of automated agents to process the query. Results and associated confidence scores can be received from the plurality of automated agents. At least some of the results and associated confidence scores can be probed, based at least on a reason given for a result having the highest associated confidence score among the received results and associated confidence scores, to select an automated agent from the plurality of automated agents for answering the query. Information can be stored, where the information can include at least the results and associated confidence scores and a selected automated agent for answering the query, where at least one of the plurality of automated agents learns from the stored information to update its confidence score in answering the query.

Abstract: A natural language input is communicated to a back end application. Candidate agent data communicated from the back end application is presented. The candidate agent data comprises data of a set of agents considered by the back end application for performance of a command extracted from the natural language input. Candidate agent score data communicated from the back end application is presented. The candidate agent score data comprises score data of an agent in the set of agents. Selected agent data communicated from the back end application is presented. The selected agent data comprises data of a selected agent in the set of agents, the selected agent selected by the back end application for performance of the command. Skill performance data communicated from the back end application is presented. The skill performance data comprises data of a processing step performed by the selected agent.

Abstract: A data visualization method, system, and computer program product that includes identifying an intent from a natural language query in a conversation with a conversational system, utilizing verbiage from the natural language query and the intent to determine one or more data columns for visualization of results of the natural language query, and displaying a visualization of the determined one or more data columns.

Abstract: A computer-implemented method of generating explanations for a sequence of actions performed by an aggregated assistant includes receiving a request from a user equipment (UE) to execute a sequence of actions. A decision is rendered on whether to execute the requested sequence of actions. An explanation regarding the rendered decision is provided including a user data upon which the decision is based.

Abstract: Computer-implemented methods, computer program products, and computer systems for improving intent determination in a messaging dialog manager system. The computer-implemented method for improving intent determination in a messaging dialog manager system may include one or more processors configured for receiving first agent entry data corresponding to a first agent communicating in a messaging dialog interface, determining that the first agent entry data expects a response that is within a first response domain, determining that a first user entry entered in the messaging dialog interface is not within the first response domain. Further, the computer-implemented may include identifying a second agent configured with a second response domain that includes the first user entry and transmitting the first user entry to the second agent to facilitate a seamless transition of an established communicational flow between the first agent and a first user.

Abstract: An optimization method, system, and computer program product for a number of tasks within a business process that can be automated that includes receiving access to an electronic representation of the business process, optimizing the business process to develop an optimized business process, displaying the optimized business process as a storyboard using storyboarding, and receiving an edit of the optimized business process, and automatically making a further edit to the optimized business process.

Abstract: A conversational interface generation method, system, and computer program product that includes determining a conversational artifact for a computer program from a specification of the computer program and generating a conversational interface for the computer program based on the conversational artifact for the computer program included in the specification.

Abstract: A computer-implemented method, a computer program product, and a computer system for explaining black-box machine learning models. A computer or server determines a process-aware neighborhood around a data sample, using one or more business process rules. The computer or server computes proximity between the process-aware neighborhood and the data sample, using a process-aware distance metric. The computer or server finds, from a family of linear functions, a local linear model, by minimizing losses of respective ones of the linear functions and a black-box machine learning model. The computer or server provides the local linear model for explanation of output of the black-box model on the data sample.

Abstract: A method, a computer program product, and a computer system orchestrate devices of a device ecosystem. The method performed by an orchestrator includes receiving polling data from agents that are directly connected to the devices indicating simulations run by the devices for a cloud service. The method comprises determining a preview state of the device ecosystem. The method comprises determining an action to change a state of the device ecosystem based on the preview state. The method comprises generating an instruction for the action and the devices to perform the action. The method comprises transmitting the instruction to the agents, the agents actuating the change via the determined at least one of the devices performing the action. The orchestrator orchestrates the agents such that the devices are provided the cloud service isolated from a cloud computing system associated with the cloud service.