US 2026/0010554 A1 · Auto-Learning Chatbot Scenarios

Abstract

A system and method for analyzing collected content from conversations between agents and end users to identify patterns and generate automated responses is disclosed. The system includes a database for storing collected content, a processing module for classifying and analyzing content, a communication interface for retrieving data via an API, and an output module for providing generated responses to users. The processing module employs various techniques, including Natural Language Processing (NLP) methods such as language detection, sentence segmentation, and part-of-speech tagging, as well as Machine Learning (ML) techniques like Naive Bayesian Classifier and clustering algorithms based on cosine similarity. The system can classify conversation content to determine if a message is a question, analyze content based on assumptions such as user-rated helpfulness, and transform the content into vector form using sentence-transformer models. It clusters the content and generates responses by identifying the most relevant response within each cluster.

Claims17

Dependent claims

A system for enabling the analysis of collected content to search for patterns and generate automated responses, the system comprising:

a database configured to store collected content, wherein the collected content comprises conversations between an agent and an end user;
a processing module configured to:
classify the content of the conversations to determine whether the sentiment of a message is a question;
analyze the classified content based on a plurality of assumptions, including selection of the most appropriate answers where the end-user rated the response as helpful, selection of the answers after which the user closed the communication, and selection of the answers after which the response from the user is immediate;
transform the classified content into vector form using a sentence-transformer model;
cluster the vectorized content based on a similarity function between sentences;
generate responses for the clustered content by identifying the most relevant and accurate response within each cluster;
an output module configured to provide the generated responses to the user;
and
a communication interface configured to retrieve data from an instant communication channel via an API.

7 more elements

Dependencies are inferred from the claim text.

Auto-Learning Chatbot Scenarios

Life of this patent

Auto-Learning Chatbot Scenarios

Life of this patent

Abstract

Claims17