Systems and methods for providing search results based on a primary intent

This invention describes a smart search system that tries to understand what a user *really* means when they type or speak a search query. It breaks down the query into potential "intention terms," figures out which one is the most important based on the surrounding words, and then uses that primary intent to deliver more relevant search results. The system is designed to work with queries from online shopping sites or apps, whether typed or spoken.

Why it matters: Filed before the widespread adoption and capabilities of large language models (LLMs) became apparent. The core tasks of identifying intent, understanding query context, and generating relevant results from natural language, which required complex custom algorithms in 2021, are now significantly more achievable and performant using off-the-shelf LLM frameworks.

Status: Not in forceListed as no longer active.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

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