A Large-scale Offer Alignment Model for Partitioning Filtering and Matching Product Offers

被引：0

作者：

Huang, Wenyu ^{[1
]}

Melo, Andre ^{[2
]}

Pan, Jeff Z. ^{[2
]}

机构：

[1] Univ Edinburgh, Edinburgh, Midlothian, Scotland

[2] Huawei Technol R&D, Edinburgh, Midlothian, Scotland

来源：

PROCEEDINGS OF THE 47TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, SIGIR 2024 | 2024年

关键词：

offer alignment; product matching; entity matching;

D O I：

10.1145/3626772.3661351

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Offer alignment is a key step in a product knowledge graph construction pipeline. It aims to align retailer offers of the same product for better coverage of product details. With the rapid development of online shopping services, the offer alignment task is applied in ever larger datasets. This work aims to build an offer alignment system that can efficiently be used in large-scale offer data. The key components of this system include: 1) common offer encoders for encoding text offer data into representations; 2) trainable LSH partitioning module to divide similar offers into small blocks; 3) lightweight sophisticated late-interactions for efficient filtering and scoring of offer alignment candidate pairs. We evaluate the system on public WDC offer alignment dataset, as well as DBLP-Scholar and DBLP-ACM.

引用

页码：2880 / 2884

页数：5

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