Attribute Value Generation from Product Title using Language Models

Kalyani Roy, Pawan Goyal, Manish Pandey


Abstract
Identifying the value of product attribute is essential for many e-commerce functions such as product search and product recommendations. Therefore, identifying attribute values from unstructured product descriptions is a critical undertaking for any e-commerce retailer. What makes this problem challenging is the diversity of product types and their attributes and values. Existing methods have typically employed multiple types of machine learning models, each of which handles specific product types or attribute classes. This has limited their scalability and generalization for large scale real world e-commerce applications. Previous approaches for this task have formulated the attribute value extraction as a Named Entity Recognition (NER) task or a Question Answering (QA) task. In this paper we have presented a generative approach to the attribute value extraction problem using language models. We leverage the large-scale pretraining of the GPT-2 and the T5 text-to-text transformer to create fine-tuned models that can effectively perform this task. We show that a single general model is very effective for this task over a broad set of product attribute values with the open world assumption. Our approach achieves state-of-the-art performance for different attribute classes, which has previously required a diverse set of models.
Anthology ID:
2021.ecnlp-1.2
Volume:
Proceedings of the 4th Workshop on e-Commerce and NLP
Month:
August
Year:
2021
Address:
Online
Editors:
Shervin Malmasi, Surya Kallumadi, Nicola Ueffing, Oleg Rokhlenko, Eugene Agichtein, Ido Guy
Venue:
ECNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
13–17
Language:
URL:
https://aclanthology.org/2021.ecnlp-1.2
DOI:
10.18653/v1/2021.ecnlp-1.2
Bibkey:
Cite (ACL):
Kalyani Roy, Pawan Goyal, and Manish Pandey. 2021. Attribute Value Generation from Product Title using Language Models. In Proceedings of the 4th Workshop on e-Commerce and NLP, pages 13–17, Online. Association for Computational Linguistics.
Cite (Informal):
Attribute Value Generation from Product Title using Language Models (Roy et al., ECNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.ecnlp-1.2.pdf