Method and system for providing context based adaptive response to user interactions

This invention describes a software system that understands what a user is trying to do and what they are talking about during an interaction. It figures out the main topic and then, if the user asks follow-up questions, it identifies sub-topics. The system keeps track of this evolving conversation context and uses it to generate helpful, tailored responses as the interaction progresses.

Why it matters: Filed before the widespread capabilities of large language models, this invention's core mechanisms for dynamic context determination and adaptive response generation are now significantly more achievable. Modern LLMs can perform intent extraction, named entity recognition, and sophisticated response generation with greater accuracy and flexibility than was practical in 2017.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, NLP models, context management

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