From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search
From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search
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Author / Creator
Li, Rui , Jiang, Yunjiang , Yang, Wenyun , Tang, Guoyu , Wang, Songlin , Ma, Chaoyi , He, Wei , Xiong, Xi , Xiao, Yun and Eric Yihong Zhao
Publisher
Ithaca: Cornell University Library, arXiv.org
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Language
English
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Publisher
Ithaca: Cornell University Library, arXiv.org
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Contents
We introduce deep learning models to the two most important stages in product search at JD.com, one of the largest e-commerce platforms in the world. Specifically, we outline the design of a deep learning system that retrieves semantically relevant items to a query within milliseconds, and a pairwise deep re-ranking system, which learns subtle user...
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Full title
From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search
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Record Identifier
TN_cdi_proquest_journals_2505020929
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2505020929
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E-ISSN
2331-8422
