The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
E-Commerce Product Categorization with LLM-based Dual-Expert Classification Paradigm
Open accessAbstract
Zhu Cheng, Wen Zhang, Chih-Chi Chou, You-Yi Jau, Archita Pathak, Peng Gao, Umit Batur. Proceedings of the 1st Workshop on Customizable NLP: Progress and Challenges in Customizing NLP for a Domain, Application, Group, or Individual (CustomNLP4U). 2024.
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Claims other papers make about this one
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In the citing paper
“Specifically, in e-commerce, a dual expert-expert classification system-that is, a domain-specific expert trained on large e-commerce domain data and a general expert managed by AI chatbotscan accurately categorize products [28].”
From Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation (2025) · cites this paper as [28]
Citations
Cites
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018) · arXiv · doi:10.48550/arxiv.1810.04805 · Cited by 73,173
Cited by
Sorted by citations
Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation
Kim, S., & Priluck, R. (2025) · Journal of Theoretical and Applied Electronic Commerce Research · doi:10.3390/jtaer20020093 · Cited by 20
“Specifically, in e-commerce, a dual expert–expert classification system—that is, a domain-specific expert trained on large e-commerce domain data and a general expert managed by AI chatbots— can accurately categorize products [28].”
Roumeliotis, K. I., Tselikas, N. D., & Nasiopoulos, D. K. (2025) · Natural Language Processing Journal · doi:10.1016/j.nlp.2025.100142 · Cited by 14
Metadata
- Authors
- Cheng, Z., Zhang, W., Chou, C.-C., Jau, Y.-Y., Pathak, A., Gao, P., & Batur, U.
- Affiliations
- Amazon (United States) (US)
- Venue
- Proceedings of the 1st Workshop on Customizable NLP: Progress and Challenges in Customizing NLP for a Domain, Application, Group, or Individual (CustomNLP4U)
- Published
- 2024
- Pages
- 294-304
- OpenAlex
- W4404784136
- Cited by
- 12
- References
- 1
- Citations by year
- 2026: 7 · 2025: 5
- FWCI
- 3.54
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Workshop on Customizable NLP: Progress and Challenges in Customizing NLP for a Domain, Application, Group, or Individual (CustomNLP4U) (publishedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Keywords
- large language models, product classification
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