Systems and methods relating to bot authoring by mining intents from natural language conversations

This invention describes a computer program designed to automatically build a conversational bot by analyzing past conversations between customers and customer service representatives. It works by identifying what customers were trying to achieve (their 'intents') from their spoken or typed words, grouping similar intents together based on meaning, and then using these grouped intents to train the bot. The program specifically extracts these intents from customer utterances within the conversation data to define the bot's understanding.

Why it matters: Filed before the widespread adoption and advanced capabilities of large language models (LLMs) were fully realized. LLMs can now significantly enhance or simplify the complex natural language processing and semantic similarity tasks required for intent mining and grouping described in the claims, potentially making the bot authoring process more efficient and accurate than previously possible.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedNatural language processing, machine learning algorithms

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