Multi-variant item search optimization via clustering algorithm

ChangeBridge: Patent Apps - Business Methods (G06Q)

Published April 2nd, 2026

Detected April 2nd, 2026

Summary

USPTO published patent application US20260094192A1 for a system and method optimizing multi-variant item search results using clustering algorithms. The invention groups similar product variants into clusters and orders display sequences based on similarity scores to reduce redundancy. Application filed October 1, 2025 by inventor Alok Goyal.

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What changed

USPTO published patent application US20260094192A1 for systems and methods of multi-variant item search result display optimization. The invention receives item search queries, determines responsive items including multiple variants of products, generates clusters where variant items are grouped together, orders items within clusters by similarity scores, and creates an optimized display sequence to reduce redundancy. CPC classifications include G06Q 30/0627 (commerce) and G06F 16/285 (information retrieval).

Patent applicants, technology companies developing search systems, and e-commerce platforms should note this published application as prior art for clustering-based search optimization technologies. No immediate compliance action is required. Parties developing similar search optimization systems may wish to conduct patent clearance analyses to assess potential infringement exposure.

Source document (simplified)

← USPTO Patent Applications

SYSTEMS AND METHODS FOR MULTI-VARIANT ITEM SEARCH RESULT DISPLAY OPTIMIZATION

Application US20260094192A1 Kind: A1 Apr 02, 2026

Inventors

Alok GOYAL

Abstract

An item search query may be received. A plurality of items responsive to the query and a plurality of similarity scores corresponding to the items may be determined. The items may include two or more item variants of a multi-variant item. A plurality of clusters, each including a subset of the items, may be generated, where at least two of the item variants are included in a same cluster. Within each cluster, a corresponding subset of the similarity scores may be associated with and used to order the subset of items within the cluster. A cluster iteration sequence may be set based on a comparison of a highest similarity score from each cluster, and a display sequence may be generated for presenting the items within an optimized user interface based on the cluster iteration sequence to reduce a display redundancy of the at least two item variants.