Using LLMs for the Extraction and Normalization of Product Attribute Values

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2016

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van Rooij, G., Sewnarain, R., Skogholt, M., van der Zaan, T., Frasincar, F., et al.: A Data Type-Driven Property Alignment Framework for Product Duplicate Detection on the Web. In: Proceedings of 17th International Web Information Systems Engineering Conference. pp. 380–395 (2016)

2016

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Zheng, G., Mukherjee, S., Dong, X.L., Li, F.: OpenTag: Open Attribute Value Extraction from Product Profiles. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. pp. 1049–1058 (2018)

2018

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2019

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Primpeli, A., Peeters, R., Bizer, C.: The WDC training dataset and gold standard for large-scale product matching. In: Companion Proceedings of The 2019 World Wide Web Conference. pp. 381–386 (2019)

2019

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Xu, H., Wang, W., Mao, X., Lan, M.: Scaling up open tagging from tens to thousands: Comprehension empowered attribute value extraction from product title. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. pp. 5214–5223 (2019)

2019

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Wang, Q., Yang, L., Kanagal, B., Sanghai, S., Sivakumar, D., et al.: Learning to extract attribute value from product via question answering: A multi-task approach. In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. pp. 47–55 (2020)

2020

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Jain, M., Bhattacharya, S., Jain, H., Shaik, K., Chelliah, M.: Learning cross-task attribute-attribute similarity for multi-task attribute-value extraction. In: Proceedings of the 4th Workshop on e-Commerce and NLP. pp. 79–87 (2021)

2021

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Valstar, N., Frasincar, F., Brauwers, G.: APFA: Automated product feature alignment for duplicate detection. Expert Systems with Applications 174

Zhang, X., Zhang, C., Li, X., Dong, X.L., Shang, J., et al.: OA-Mine: Open-World Attribute Mining for E-Commerce Products with Weak Supervision. In: Proceedings of the ACM Web Conference 2022. pp. 3153–3161 (2022)

2022

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Blume, A., Zalmout, N., Ji, H., Li, X.: Generative Models for Product Attribute Extraction. In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track. pp. 575–585 (2023)

2023

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Brinkmann, A., Shraga, R., Bizer, C.: Product Attribute Value Extraction using Large Language Models. arXiv preprint arXiv:2310.12537 (2023)

Original

2023

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Goel, A., Gueta, A., Gilon, O., Liu, C., Erell, S., et al.: LLMs Accelerate Annotation for Medical Information Extraction. In: Proceedings of the 3rd Machine Learning for Health Symposium. pp. 82–100 (2023)

2023

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