Hierarchical Knowledge Graph Construction from Images for Scalable E-Commerce

• URL: http://arxiv.org/abs/2410.21237v1
• Date: Mon, 28 Oct 2024 17:34:05 GMT
• Title: Hierarchical Knowledge Graph Construction from Images for Scalable E-Commerce
• Authors: Zhantao Yang, Han Zhang, Fangyi Chen, Anudeepsekhar Bolimera, Marios Savvides,
• Abstract summary: 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)
• Score: 17.97354500453661
• License:
• 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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