Multimodal Joint Attribute Prediction and Value Extraction for E-commerce Product
Tiangang Zhu, Yue Wang, Haoran Li, Youzheng Wu, Xiaodong He, Bowen Zhou
Abstract
Product attribute values are essential in many e-commerce scenarios, such as customer service robots, product recommendations, and product retrieval. While in the real world, the attribute values of a product are usually incomplete and vary over time, which greatly hinders the practical applications. In this paper, we propose a multimodal method to jointly predict product attributes and extract values from textual product descriptions with the help of the product images. We argue that product attributes and values are highly correlated, e.g., it will be easier to extract the values on condition that the product attributes are given. Thus, we jointly model the attribute prediction and value extraction tasks from multiple aspects towards the interactions between attributes and values. Moreover, product images have distinct effects on our tasks for different product attributes and values. Thus, we selectively draw useful visual information from product images to enhance our model. We annotate a multimodal product attribute value dataset that contains 87,194 instances, and the experimental results on this dataset demonstrate that explicitly modeling the relationship between attributes and values facilitates our method to establish the correspondence between them, and selectively utilizing visual product information is necessary for the task. Our code and dataset are available at https://github.com/jd-aig/JAVE.- Anthology ID:
- 2020.emnlp-main.166
- Volume:
- Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Bonnie Webber, Trevor Cohn, Yulan He, Yang Liu
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2129–2139
- Language:
- URL:
- https://aclanthology.org/2020.emnlp-main.166
- DOI:
- 10.18653/v1/2020.emnlp-main.166
- Cite (ACL):
- Tiangang Zhu, Yue Wang, Haoran Li, Youzheng Wu, Xiaodong He, and Bowen Zhou. 2020. Multimodal Joint Attribute Prediction and Value Extraction for E-commerce Product. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 2129–2139, Online. Association for Computational Linguistics.
- Cite (Informal):
- Multimodal Joint Attribute Prediction and Value Extraction for E-commerce Product (Zhu et al., EMNLP 2020)
- PDF:
- https://preview.aclanthology.org/corrections-2024-05/2020.emnlp-main.166.pdf
- Code
- jd-aig/JAVE + additional community code