@inproceedings{chen-miyake-2021-label,
title = "Label-Guided Learning for Item Categorization in e-Commerce",
author = "Chen, Lei and
Miyake, Hirokazu",
editor = "Kim, Young-bum and
Li, Yunyao and
Rambow, Owen",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Papers",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.naacl-industry.37",
doi = "10.18653/v1/2021.naacl-industry.37",
pages = "296--303",
abstract = "Item categorization is an important application of text classification in e-commerce due to its impact on the online shopping experience of users. One class of text classification techniques that has gained attention recently is using the semantic information of the labels to guide the classification task. We have conducted a systematic investigation of the potential benefits of these methods on a real data set from a major e-commerce company in Japan. Furthermore, using a hyperbolic space to embed product labels that are organized in a hierarchical structure led to better performance compared to using a conventional Euclidean space embedding. These findings demonstrate how label-guided learning can improve item categorization systems in the e-commerce domain.",
}
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%0 Conference Proceedings
%T Label-Guided Learning for Item Categorization in e-Commerce
%A Chen, Lei
%A Miyake, Hirokazu
%Y Kim, Young-bum
%Y Li, Yunyao
%Y Rambow, Owen
%S Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Papers
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F chen-miyake-2021-label
%X Item categorization is an important application of text classification in e-commerce due to its impact on the online shopping experience of users. One class of text classification techniques that has gained attention recently is using the semantic information of the labels to guide the classification task. We have conducted a systematic investigation of the potential benefits of these methods on a real data set from a major e-commerce company in Japan. Furthermore, using a hyperbolic space to embed product labels that are organized in a hierarchical structure led to better performance compared to using a conventional Euclidean space embedding. These findings demonstrate how label-guided learning can improve item categorization systems in the e-commerce domain.
%R 10.18653/v1/2021.naacl-industry.37
%U https://aclanthology.org/2021.naacl-industry.37
%U https://doi.org/10.18653/v1/2021.naacl-industry.37
%P 296-303
Markdown (Informal)
[Label-Guided Learning for Item Categorization in e-Commerce](https://aclanthology.org/2021.naacl-industry.37) (Chen & Miyake, NAACL 2021)
ACL
- Lei Chen and Hirokazu Miyake. 2021. Label-Guided Learning for Item Categorization in e-Commerce. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Papers, pages 296–303, Online. Association for Computational Linguistics.