Method and system for probabilistically quantifying and visualizing relevance between two or more citationally or contextually related data objects

This invention describes a search engine that finds and ranks documents based on how they cite each other. It specifically looks for connections that are three to five steps away in the citation chain, then calculates a relevance score by adding up individual citation scores. The system can also create visual maps to help users understand these complex relationships.

Why it matters: Filed before advanced graph databases and large language models made complex relational analysis and contextual understanding significantly more accessible and powerful. These modern tools could simplify the implementation of the probabilistic models and enhance the visualization capabilities described.

Status: Not in forceListed as no longer active.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 infrastructure, complex algorithms

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