Abstract
An electronic search system and method process multi-dimensional shopping queries by executing a real-time union of multi-aspect parameters across multiple web domains. The system receives a user query specifying a product and multiple desired characteristics. Rather than relying on a static, pre-existing search index or database, a backend processing pipeline takes live uniform resource locators (URLs) generated from a primary parallel search. The system dynamically navigates to these specific product pages in real-time to extract and analyze unindexed user review data on the fly. By performing semantic keyword analysis across disparate vendor sites, the backend skill evaluates the intersection of the query conditions to generate highly targeted results ranked by combined relevancy scores.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Wolf, Lois, "Optimizing Shopping Search Using Artificial Intelligence by Separating and Recombining Search Terms", Technical Disclosure Commons, (July 27, 2026)
https://www.tdcommons.org/dpubs_series/11149