Generating search results based on clustered application states

This invention describes a search engine that helps users find specific software applications. It works by looking at the different "states" an application can be in (like what it's doing or the data it's showing) and groups these states into clusters based on how people use them, their popularity, or location. When you search, it finds relevant applications and scores them higher if their states match the search and belong to relevant clusters.

Why it matters: Filed before advanced machine learning and big data platforms made large-scale, real-time clustering of application states based on diverse usage data and features (like popularity and geography) significantly more efficient and accurate. Modern AI can now more effectively derive and group these states.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, data processing, clustering algorithms

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