2021 · 22 citations · 16 references
BusinessComputer ScienceInformation SystemsCategory ManagementE-commerce SystemsInformation RetrievalCategory SegmentationClassificationClassification SchemesProduct ClassificationTaxonomyCategory ErrorCategory Hierarchy ConstructionGranularityHierarchyListing StrategyProduct Category ManagementProduct Type Identification
E-commerce platforms often use a predefined structured hierarchy of product categories. Apart from helping buyers sort between different product types, listing categorization is also critical for multiple downstream tasks, including the platform's main listing search. Traditionally, when creating a new listing, sellers need to assign the product they sell to a single category. However, the high diversity of product types in the platform, along with the hierarchy's low level of granularity result in tens of thousands of different possible categories that sellers need to pick from. This, in turn, creates a unique classification challenge, especially for sellers with a large number of listings. Moreover, the expected cost of making a category classification error is high, as it can impact the likelihood that their listing will get discovered by relevant buyers, and eventually sold.
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Ashish Vaswani, Noam Shazeer, Niki Parmar et al. · 2025 · 6.6K citations · Full text
Sequence to Sequence Learning with Neural Networks
Ilya Sutskever, Oriol Vinyals, Quoc V. Le · arXiv (Cornell University) · 2014 · 3.5K citations · Full text
Computing, Computer Science, French +14
Convolutional Sequence to Sequence Learning
Jonas Gehring, Michael Auli, David Grangier et al. · arXiv (Cornell University) · 2017 · 1.9K citations · Full text