- New York NY, US Luis BEAUMIER - St. Petersburg FL, US Marc NADEAU - St. Petersburg FL, US Ryan EDLEY - Chicago IL, US Robert COEN - Tampa FL, US Jason Victor RANDALL - Dunedin FL, US Shannon M. ROBINSON - Memphis TN, US
Assignee:
PricewaterhouseCoopers LLP - New York NY
International Classification:
G06F 16/2455 G06F 16/242 G06F 16/22
Abstract:
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
- New York NY, US Luis BEAUMIER - St. Petersburg FL, US Marc NADEAU - St. Petersburg FL, US Ryan EDLEY - Chicago IL, US Robert COEN - Tampa FL, US Jason Victor RANDALL - Dunedin FL, US Shannon M. ROBINSON - Memphis TN, US
Assignee:
PricewaterhouseCoopers LLP - New York NY
International Classification:
G06F 16/9032 G06F 16/9038 G10L 15/26
Abstract:
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.
- New York NY, US Luis BEAUMIER - St. Petersburg FL, US Marc NADEAU - St. Petersburg FL, US Ryan EDLEY - Chicago IL, US Robert COEN - Tampa FL, US Jason Victor RANDALL - Dunedin FL, US Shannon M. ROBINSON - Memphis TN, US
Assignee:
PricewaterhouseCoopers LLP - New York NY
International Classification:
G06F 40/40 G06N 5/02 G06F 3/0482 G06F 3/16
Abstract:
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.
Picker Memphis, TN May 2013 to Apr 2014 AuditorKelly Services Memphis, TN Jul 2011 to Feb 2012 CaregiverShelby's Guardian Angels Canton, OH May 2010 to Nov 2010 In-home caregiverFedEx Hub Memphis, TN Aug 2007 to Aug 2009 Material HandlerBurger King Memphis, TN Jul 2003 to May 2006 Team Leader
Education:
Concord Career College Memphis, TN Aug 2007 to Apr 2008 Diploma in Management and Bartending-CerificateMassillon Washington High School Massillon, OH Aug 1999 to Jun 2003 Diploma in General Studies
Murtuza Ali, Jimmy Glenn, Jessica Walters, Megan Exline, Brian Thomas, Adam Smith, Shane Sanders, Jim Nicholson, Heather Nabors, Bobby Hart, Amanda Miller, Scott Cobb
Biography:
hello my name is shannon powers i have 2 beautiful girls i bacame a proud parent 4/1...
Longridge Elementary School Rochester NY 1980-1984, Barnard Elementary School Rochester NY 1984-1986, Hoover Drive Junior High School Rochester NY 1986-1989
A big part of keeping children safe is clear communication between the educators and parents, said Shannon Robinson, health and nutrition manager at the child care non-profit Bright Beginnings in Washington, D.C.