Hierarchical Knowledge Graph Construction from Images for Scalable E-Commerce

Zhantao Yang; Han Zhang; Fangyi Chen; Anudeepsekhar Bolimera; Marios Savvides

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arXiv · 2410.21237

Hierarchical Knowledge Graph Construction from Images for Scalable E-Commerce

Zhantao Yang·Han Zhang·Fangyi Chen·Anudeepsekhar Bolimera·Marios Savvides

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Abstract

Knowledge Graph (KG) is playing an increasingly important role in various AI systems. For e-commerce, an efficient and low-cost automated knowledge graph construction method is the foundation of enabling various successful downstream applications. In this paper, we propose a novel method for constructing structured product knowledge graphs from raw product images. The method cooperatively leverages recent advances in the vision-language model (VLM) and large language model (LLM), fully automating the process and allowing timely graph updates. We also present a human-annotated e-commerce product dataset for benchmarking product property extraction in knowledge graph construction. Our method outperforms our baseline in all metrics and evaluated properties, demonstrating its effectiveness and bright usage potential.

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Zhantao Yang, Han Zhang, Fangyi Chen, Anudeepsekhar Bolimera, Marios Savvides. 2024-10-28. Hierarchical Knowledge Graph Construction from Images for Scalable E-Commerce. https://arxiv.org/abs/2410.21237

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