Receive a question via a graphical user interface (GUI), obtain a passage of text potentially relevant to the question, and receive, via the GUI, a selection of a number of question-answering models to be ensembled. Produce a plurality of answers to the question by running a plurality of question-answering models, consistent with the selection of the number of question-answering models to be ensembled, on the passage of text. Produce an ensembled answer by ensembling the plurality of answers according to their respective confidence scores. Display, via the GUI, the ensembled answer in context of the passage of text, with the ensembled answer visually marked in the passage of text. Optionally, repeat these steps for a second passage of text.

The present disclosure relates to an information system, a method of providing information, and a respective electronic device. The electronic device is operable to provide an information to a user being indicative of a user device. The electronic device comprises: a processor to process a user request, a user interface to communicate with the user, and an electronic storage connected to the processor. The processor is operable: to extract at least one keyword from the user request, to select at least one information content from a content database on the basis of the at least one extracted keyword, and to provide the at least one selected information content to the user via the user interface.

A method for receiving a historical incident data set with the historical incident data set including a plurality of data records, for each given data record of the plurality of data records, applying a causal analysis algorithm to determine a set of causal factor(s) for the historical instance of an incident corresponding to the given data record to obtain a problems and solutions data set, and automatically, and by machine logic, generating a chatbot based, at least in part, on the problems and solutions data set.

Systems and methods are disclosed for a specialized warranty bot that can interact with users to evaluate warranty coverage. A warranty interpreter interprets warranty aspects of a given system and converts the warranty terms it into human understandable text. A situation analyzer enhances warranty interpretation by scanning logs across various components that are covered by the warranty and identifying whether the current problems are covered by the warranty. Assessment guidance processing anticipates questions from the customer and provides information regarding why a problem may not be covered by the warranty. Using a solution advisor, based on the problem details and historical analysis, the warranty bot provides insights regarding potential minimum time for resolution of a problem in order to assist the user to decide whether the system needs to be isolated or if the system can remain in production in a non-critical path.

The present disclosure is generally directed to the generation of domain-specific, voice-activated systems in interconnected networks. The system can receive input signals that are detected at a client device. The input signals can be voice-based input signals, text-based input signals, image-based input signals, or other type of input signals. Based on the input signals, the system can select domain-specific knowledge graphs and generate responses based on the selected knowledge graph.

Programs, systems, and methods for generating a support tree for automated resolution of user issues. In some embodiments, historical data may be obtained from a history of support interactions including historical issues and solutions to the historical issues. Most used solutions may be determined and stored with associated historical issues. Clusters of issues and solutions may be generated and labeled for generation of support tree nodes. Furthermore, solutions may be correlate such that a plurality of solutions may be provided for the resolving user issues. In some embodiments, issue data indicative of user issues may be provided by users. As the user provides issue data, deflections between nodes on the support tree may narrow a field of potential solutions to one or more solutions to be provided to the user.

Disclosed is a technical solution to reduce latency in reader-retriever architectures of an open domain query response system. An example apparatus is to reduce latency in a retriever-reader architecture comprising at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to identify a query, the query having data associated with the query, create a data array based on the data associated with the query, and deploy a machine learning model. The machine learning model is to assign a score to an index of the data array based on a likelihood that a response to the query exists in the index, determine an action to perform on the index based on a comparison of the score and a ranking threshold, and produce the response from the data array based on the action.

Techniques are described herein for enabling autonomous agents to generate conclusive answers. An example of a conclusive answer is text that addresses concerns of a user who is interacting with an autonomous agent. For example, an autonomous agent interacts with a user device, answering user utterances, for example questions or concerns. Based on the interactions, the autonomous agent determines that a conclusive answer is appropriate. The autonomous agent formulates the conclusive answer, which addresses multiple user utterances. The conclusive answer provided to the user device.

According to one embodiment, the interface-providing apparatus comprises an identifying unit and a generating unit. The identifying unit identifies a keyword from dialogue data including a question text to request information, and a response text in reply thereto. The generating unit generates display information to display a user interface for receiving feedback input relating to a degree of usefulness of a keyword when searching for the requested information.

A computing device may represent dialog for output by a chatbot as a response graph. The graph may consist of nodes and edges, both of which may have attributes. The graph may be linked with another graph. There may be one or more traversal paths through the graph. The computing device may represent each traversal path as a row in a database table. Each column in the table row may correspond to: one or more nodes in the traversal path, a condition value, weight, and/or other filtering condition. A computing device may display a graphical user interface that allows a user to add, edit, and/or delete nodes and/or edges of the graph. The user interface may also allow the user to compare two or more graphs. The user interface may generate visualizations of traversal paths of a response graph.