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- W3170232411 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." @default.
- W3170232411 created "2021-06-22" @default.
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- W3170232411 date "2021-01-01" @default.
- W3170232411 modified "2023-10-16" @default.
- W3170232411 title "Label-Guided Learning for Item Categorization in e-Commerce" @default.
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- W3170232411 doi "https://doi.org/10.18653/v1/2021.naacl-industry.37" @default.
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