Methods and systems that predict future actions from instrumentation-generated events

This invention describes a computer system that observes user actions online, like clicks or page visits. It uses advanced statistical methods, specifically a hidden-variable model, to interpret these actions and discover underlying patterns. By understanding these patterns, the system can predict future user behavior, which is useful for applications like targeted advertising. The claims specifically detail a computer-implemented method for using a hidden-variable model to generate enhanced action messages.

Why it matters: Filed before the widespread adoption of advanced machine learning frameworks and cloud-based data processing. Modern MLOps practices and more powerful probabilistic modeling techniques make building and deploying such predictive systems, especially those using hidden-variable models for sequential data, significantly more efficient and scalable today.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedComplex software, statistical modeling, data pipelines

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