Moveworks, Inc.

Chang Liu

Jiang Chen

Ye Wang

Jing Chen

A disambiguation dialog may be generated by determining candidate responses based on an intent of a user's message. A utility value and a relevance probability may be determined for each of the candidate responses. An intermediate ranking may be computed for each of the candidate responses based on the utility value and the relevance probability. Candidate dialogs may be formed with the top candidate response, the top two candidate responses, and so on. Additional candidate dialogs may be generated by varying a presentation format of the candidate responses. Discoverability probabilities may be associated with each of the candidate responses within a candidate dialog. A joint metric for each candidate dialog may be computed as a function of the utility value, relevance probability and discoverability probability associated with each of the candidate responses included in the candidate dialog. The highest ranked candidate dialog may be selected as the disambiguation dialog.

Generic disambiguation

An automated conversation is facilitated between a user and a virtual agent. A system receives an input message from the user and analyzes an intent of the input message. Based on the intent of the input message, the system generates a plurality of bids for responding to the input message, and assigns an intent confidence score to each bid from the plurality of bids based on a confidence level of each bid from the plurality of bids. The system determines a winning bid from the plurality of bids based on the intent confidence score associated with each bid from the plurality of bids, and generates a response based on the winning bid.

Virtual conversation method or system

A computer-implemented method for training a chatbot is provided. The method includes receiving a training input through a platform associated with the chatbot. The training input indicates user intent for interacting with the chatbot. The method includes calculating a confidence score associated with a prediction of the user intent identified by the chatbot. The method further includes providing a training score to the user providing the training input based on the confidence score.

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Mountain View, CA, United States of America

Chang Liu