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US 2026/0300284 A1Published application
Hierarchical Learning for Information Retrieval and Exploration
OwnerSathya Narayan Reddyinventor
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OwnerSathya Narayan Reddyinventor
Estimating the term…
A computer-implemented method for information retrieval is disclosed in which a structured relational model is learned from domain-associated data. The learned model defines admissible multi-entity interaction configurations, including unary, binary, and higher-order n-ary configurations, subject to domain constraints. A natural language query is received and transformed into a structured query representation comprising at least one fully or partially specified multi-entity relational configuration. The structured query representation may include unspecified relational roles. The system identifies configuration regions within the structured relational model that are compatible with the structured query representation and retrieves information from an information store based on the identified configuration regions. In certain implementations, the structured relational model includes relational sections organized in a hierarchical refinement structure, supports algebraic operations over configuration regions, and enforces consistency across overlapping multi-entity configurations. Retrieval is performed with respect to admissible relational configurations rather than solely matching stored relational instances.
A computer-implemented method for information retrieval, comprising:
A system for information retrieval, comprising:
A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors, cause the one or more processors to:
Dependencies are inferred from the claim text.