International Business Machines Corporation

Courtney Branson

Andrew Ronald Freed

Sorabh Murgai

Aaron T Smith

Daniel Margulis

Marquis Hackett

Embodiments relate to a system, program product, and method for use with an intelligent computer platform and cognitive processing. The embodiments support a mechanism for employing machine learning into dynamically processing a file. File data points are converted to vector form and augmented with similar or synonymous terms. The vector representations of the data points are utilized to identify words and their frequencies, and the identified frequencies are extrapolated and applied to the synonymous terms. As communications are received, the ML model converts the communication to vector form, and compares a feature vector of the communication with data point or file feature vectors to identify and map the communication to a similarly classified file.

Augmentation of a text representation model

Embodiments for managing chatbots are provided. Chatbot interaction information is received. At least one chatbot interaction within the received chatbot interaction information is identified. The at least one identified chatbot interaction includes an initial utterance provided by a user, an unsuccessful response generated responsive to the initial utterance, a subsequent utterance provided by the user, and a successful response generated responsive to the subsequent utterance. The successful response is associated with a chatbot intent. A confidence score for associating the initial utterance with utilization of the chatbot intent by a chatbot is calculated.

Methods and systems for improving chatbot intent training by correlating user feedback provided subsequent to a failed response to an initial user intent

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Raleigh, NC, United States of America

Courtney Branson