Pricewaterhousecoopers Llp

Pwc Product Sales LLC

Ryan Edley

Suneet Dua

Robert Coen

Jason Victor Randall

Shannon M Robinson

Luis Beaumier

Marc R Nadeau

Marc Nadeau

Described herein are systems, methods, and graphical user interfaces for creating conversation models that may be executed by natural language understanding systems and/or intelligent assistant systems, particularly in enterprise and corporate environments. A conversation modeling interface may allow a modeler to position a plurality of graphical conversation-element objects on a canvas region of the interface, to specify associations and relationships between the various represented conversation-elements to define a conversation flow, and to provide input data to define various parameters and characteristics of the conversation-elements of the conversation. The system may generate and store a conversation model based on the visual representation of the conversation model created in the modeling interface, and functionality of the conversation model may be configured in accordance with the conversation-element types positioned on the canvas region, the relationships and links defined between the various elements, and the data input with respect to the various elements.

Systems and methods for conversation modeling

Systems and methods for processing natural language inputs to determine user intents using an insights repository are provided. An insights repository system is configured to build an insights repository as a data structure representing a plurality of entities and relationships among those various entities. The insights repository system may receive information from various sources via an event stream, and may process the information using event rules. Based on the application of the event rules, the system may configure an insights repository data structure representing various entities, relationships between various entities, and the strengths of relationships between various entities. After the insights repository is created, consumers may execute queries against the insights repository. Furthermore, the insights repository system may automatically query the insights repository to generate insight information to be published to an insight feed to which consumer systems may subscribe to receive automatic updates.

Systems and methods for automatically determining utterances, entities, and intents based on natural language inputs

A language understanding system is configured to process utterances to predict intents of users, including by suggesting utterances and intents based on searches performed by one or more microservices. A central service is configured to receive inputs/queries from a user, to communicate with a plurality of language processing microservices, and to return a response to the user. The microservices may be configured to apply respective search algorithms comparing the input to respective data sources such as databases, indexes, or knowledge graphs. The microservices may rate utterances and/or entities in the respective data sources with respect to the input. The one or more microservices may generate a ranked list and return the ranked list to the central service. The central service may then apply a secondary rating/ranking algorithm in order to select one or more predicted utterances and/or entities to return to the user based on the initial user input.

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Chicago, IL, United States of America

Ryan Edley