Verbesserung der Einrastung in Bezug auf Abfrage

Details

Veröffentlichungs-Nr.

EP4800574

Anmeldetag

20. Februar 2026

Veröffentlichung

2. September 2026

Rechtsraum

EP

IPC

G06F16/9032, G06F16/9536

Abstract

Methods, systems, and computer media are disclosed for generating enhanced query suggestions by integrating collaborative filtering, embedding-based similarity, and large language model generation techniques. The system accesses a query keyword and produces three types of suggestions: one derived from historical user behavior, one based on semantic similarity using embeddings, and one generated by an LLM. These suggestions are stored in association with the query keyword and may be retrieved for future queries. For new or previously unseen queries, the system generates a semantic hash and identifies the most similar stored keyword using hash comparison or embedding similarity. The technology improves upon traditional collaborative filtering by enabling relevant and diverse suggestions even for low-frequency or non-head queries. This approach enhances user engagement and search effectiveness on e-commerce platforms by aligning suggestions more closely with user intent, regardless of historical data availability. The system supports scalable, real-time performance across large query datasets.

Anmelder

Firma

eBay Inc.

Land

🇺🇸 USA

Fachgebiete