Graph-based Multilingual Product Retrieval in E-commerce Search
| Autor: | Lu, Hanqing, Hu, Youna, Zhao, Tong, Wu, Tony, Song, Yiwei, Yin, Bing |
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| Rok vydání: | 2021 |
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| Druh dokumentu: | Working Paper |
| Popis: | Nowadays, with many e-commerce platforms conducting global business, e-commerce search systems are required to handle product retrieval under multilingual scenarios. Moreover, comparing with maintaining per-country specific e-commerce search systems, having a universal system across countries can further reduce the operational and computational costs, and facilitate business expansion to new countries. In this paper, we introduce a universal end-to-end multilingual retrieval system, and discuss our learnings and technical details when training and deploying the system to serve billion-scale product retrieval for e-commerce search. In particular, we propose a multilingual graph attention based retrieval network by leveraging recent advances in transformer-based multilingual language models and graph neural network architectures to capture the interactions between search queries and items in e-commerce search. Offline experiments on five countries data show that our algorithm outperforms the state-of-the-art baselines by 35% recall and 25% mAP on average. Moreover, the proposed model shows significant increase of conversion/revenue in online A/B experiments and has been deployed in production for multiple countries. Comment: Accepted by 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021) |
| Databáze: | arXiv |
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