Abstract
An automated data processing system and computer-implemented method are disclosed for programmatically synthesizing novel structural architectures in a vacant target domain space utilizing the invariant physical or structural laws of a highly validated source domain. The system executes a generative forward loop by extracting an ordered tuple of structural and functional mechanics from a source domain, removing forward-validation lexicon filters, and enforcing aggressive semantic isolation and lexical pruning to block known industry-specific terms. Forced into a vector space void, an optimization engine or generative model synthesizes a structurally constrained neologism and an associated set of invented mechanisms. The system then executes an automated validation reverse loop by feeding the fabricated target framework back into a highly restricted back-mapping engine. This engine measures vocabulary demolition, structural back-mapping accuracy, and isomorphic invariance against the operational laws of the original source domain to dynamically separate random semantic noise from valid, structurally sound breakthroughs. The disclosed technology provides architectural enhancements to the data-searching logic described in US Pat. No. 6,523,026.
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Recommended Citation
Gillis, Herbert, "SYSTEM AND AUTOMATED METHOD FOR ISOMORPHIC CONCEPT DISCOVERY AND CROSS-DOMAIN ARCHITECTURAL SYNTHESIS VIA CONTROLLED HALLUCINATION AND REVERSE CONSTRAINED MAPPING: vector-isolated RAG pipeline and bi-directional optimization loop for open-domain structural analogy generation.", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/12070