Verint Americas Inc.

Next It Corporation

Learn.com, Inc.

Next It Innovation Labs, LLC

Learn2 Corporation

Mark Zartler

Tanya M Miller

Fred A Brown

Robert Michael Hust

Scott Buzan

Michael Thenhaus

Richard Merrick

Wesley Bell

Molly Q Brown

Virtual assistants intelligently emulate a representative of a service provider by providing variable responses to user queries received via the virtual assistants. These variable responses may take the context of a user's query into account both when identifying an intent of a user's query and when identifying an appropriate response to the user's query.

Method of using a virtual assistant

Various embodiments are described for searching and retrieving documents based on a natural language input. A computer-implemented natural language processor electronically receives a natural language input phrase from an interface device. The natural language processor attributes a concept to the phrase with the natural language processor. The natural language processor searches a database for a set of documents to identify one or more documents associated with the attributed concept to be included in a response to the natural language input phrase. The natural language processor maintains the concepts during an interactive session with the natural language processor. The natural language processor resolves ambiguous input patterns in the natural language input phrase with the natural language processor. The natural language processor includes a processor, a memory and/or storage component, and an input/output device.

Apparatus, system, and method for natural language processing

Various embodiments are described which leverage techniques for breaking down critical ideas from an inputted phrase into concepts in order to provide a response that is more relevant to the inputted phrase. In this regard, concepts and/or concept patterns are utilized with information retrieval searching to provide more relevant and concise documents in response to an inputted phrase. In addition, concepts and/or concept patterns are utilized with respect to assessing information (e.g., documents) available in a knowledge base and building appropriate pre-defined responses to an inputted phrase.

Leveraging concepts with information retrieval techniques and knowledge bases

Providing variable responses in a virtual-assistant environment

User intent may be derived from a previous communication. For example, a text string for user input may be obtained. The text string may include a pronoun. Information from a communication received prior to receipt of the user input may be derived. The information may identify an individual. User intent may be derived from the text string and the information. This may include determining that the pronoun refers to the individual.

Deriving user intent from a prior communication

A virtual assistant may communicate with a user in a natural language that simulates a human. The virtual assistant may be associated with a human-configured knowledge base that simulates human responses. In some instances, a parent response may be provided by the virtual assistant and, thereafter, a child response that is associated with the parent response may be provided.

Virtual assistant conversations

A virtual assistant may communicate with a user in a conversational manner based on context. For instances, a virtual assistant may be presented to a user to enable a conversation between the virtual assistant and the user. A response to user input that is received during the conversation may be determined based on contextual values related to the conversation or system that implements the virtual assistant.

Context-based virtual assistant conversations

Various embodiments provide a tool, referred to herein as 'Active Lab' that can be used to develop, debug, and maintain knowledge bases. These knowledge bases (KBs) can then engage various applications, technology, and communications protocols for the purpose of task automation, real time alerting, system integration, knowledge acquisition, and various forms of peer influence. In at least some embodiments, a KB is used as a virtual assistant that any real person can interact with using their own natural language. The KB can then respond and react however the user wants: answering questions, activating applications, or responding to actions on a web page.

Regression testing

Virtual agents may be implemented on a wearable device. The wearable device may include an input device to receive input and a communication component to send the input to a computing device for processing and to receive a response for the input. The wearable device may also include an output device to output the response via the virtual agent as part of a conversation with a user.

Wearable-based virtual agents

Ambiguous input of a user received during an interactive session with a virtual agent may be processed. The virtual agent may be presented via a computing device to facilitate the interactive session with the user. The user may provide the ambiguous input, which is processed to determine a response to the input. The virtual agent may provide the response to the user. The virtual agent may also carry out a goal-based dialogue where a goal to be accomplished is identified. The virtual agent may prompt the user for information related to the goal.

Virtual assistant conversations for ambiguous user input and goals

Various embodiments provide a state-based, regular expression parser in which data, such as generally unstructured text, is received into the system and undergoes a tokenization process which permits structure to be imparted to the data. Tokenization of the data effectively enables various patterns in the data to be identified. In some embodiments, one or more components can utilize stimulus/response paradigms to recognize and react to patterns in the data.

Growing community of inventors

Garland, TX, United States of America

Mark Zartler