Abstract
This document describes a query augmentation technique designed to enhance machine learning performance in local search online retrieval. Online retrieval tasks in local search involve retrieving relevant information such as review snippets, images/videos, points of interest, merchant posts, and short videos in response to a user's query. The challenge lies in the need for substantial training data to effectively train machine learning models for these diverse retrieval tasks. This document details a solution that leverages the structure of local search queries and large language models to generate augmented training data, leading to improved retrieval performance.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Nguyen, Huy Thong, "Local Search Query Augmentation for Improved Online Retrieval Performance", Technical Disclosure Commons, (April 30, 2025)
https://www.tdcommons.org/dpubs_series/8055