Systems and methods relating to bot authoring by mining intents from conversation data via intent seeding

This invention describes a computer program that helps build conversational bots. It works by taking existing customer service conversations and a few example phrases for what a bot should understand (called 'seed intents'). The program then analyzes the conversations to find more phrases that mean the same thing as the examples, using techniques like checking word meanings and sentence structure. Finally, it adds these newly found phrases to the bot's understanding, making it smarter.

Why it matters: The patent details specific NLP techniques like syntactic parsing and POS tagging for intent mining. Since 2021, large language models have dramatically advanced, offering more robust and flexible methods for semantic understanding and intent extraction, potentially simplifying or enhancing the core goal of this invention.

Status: Not in forceListed as no longer active.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, bot integration

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