Event detection through text analysis using dynamic self evolving/learning module

This invention describes a way to find out when events happen by analyzing information from various sources, like text. It works by giving scores to important words or phrases, adjusting those scores based on how often they appear, and then flagging a potential event if the score passes a certain level. It can also group these words or phrases and score them against different event patterns.

Why it matters: Filed before the widespread adoption of powerful large language models (LLMs). These models can now significantly enhance the "dynamic self evolving/learning" aspect and improve the accuracy of feature extraction and event detection described in the claims.

Status: Not in forceListed as no longer active.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

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