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 preferences. Compared to traditional search systems, the proposed approaches are better at semantic retrieval and personalized ranking, achieving significant improvements.

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References

[1]

Tianqi Chen and Carlos Guestrin. 2016. XGBoost: A Scalable Tree Boosting System. In KDD. 785--794.

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Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, and Larry Heck. 2013. Learning deep structured semantic models for web search using clickthrough data. In CIKM. 2333--2338.

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Zhang JGao WJia Y(2023)WES-BTM: A Short Text-Based Topic Clustering ModelSymmetry10.3390/sym1510188915:10(1889)Online publication date: 9-Oct-2023
https://doi.org/10.3390/sym15101889
Guo JCai YFan YSun FZhang RCheng X(2022)Semantic Models for the First-Stage Retrieval: A Comprehensive ReviewACM Transactions on Information Systems10.1145/348625040:4(1-42)Online publication date: 24-Mar-2022
https://dl.acm.org/doi/10.1145/3486250
Xiao ZJiang YTang GLiu LXu SXiao YYan W(2021)Adversarial Mixture Of Experts with Category Hierarchy Soft Constraint2021 IEEE 37th International Conference on Data Engineering (ICDE)10.1109/ICDE51399.2021.00278(2453-2463)Online publication date: Apr-2021
https://doi.org/10.1109/ICDE51399.2021.00278
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Index Terms

From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search
1. Information systems
  1. Information retrieval

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Published In

SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2019

1512 pages

ISBN:9781450361729

DOI:10.1145/3331184

General Chairs:
Benjamin Piwowarski
CNRS - Sorbonne Universite, France
,
Max Chevalier
Universite de Toulouse, CNRS, France
,
Eric Gaussier
Universite Grenoble Alpes, CNRS, France
,
Program Chairs:
Yoelle Maarek
Amazon Research, Israel
,
Jian-Yun Nie
University of Montreal, Canada
,
Falk Scholer
RMIT University, Australia

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 18 July 2019

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SIGIR '19: The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

July 21 - 25, 2019

Paris, France

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SIGIR'19 Paper Acceptance Rate 84 of 426 submissions, 20%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Zhang JGao WJia Y(2023)WES-BTM: A Short Text-Based Topic Clustering ModelSymmetry10.3390/sym1510188915:10(1889)Online publication date: 9-Oct-2023
https://doi.org/10.3390/sym15101889
Guo JCai YFan YSun FZhang RCheng X(2022)Semantic Models for the First-Stage Retrieval: A Comprehensive ReviewACM Transactions on Information Systems10.1145/348625040:4(1-42)Online publication date: 24-Mar-2022
https://dl.acm.org/doi/10.1145/3486250
Xiao ZJiang YTang GLiu LXu SXiao YYan W(2021)Adversarial Mixture Of Experts with Category Hierarchy Soft Constraint2021 IEEE 37th International Conference on Data Engineering (ICDE)10.1109/ICDE51399.2021.00278(2453-2463)Online publication date: Apr-2021
https://doi.org/10.1109/ICDE51399.2021.00278
Qiu YZhang KZhang HWang SXu SXiao YLong BYang W(2021)Query Rewriting via Cycle-Consistent Translation for E-Commerce Search2021 IEEE 37th International Conference on Data Engineering (ICDE)10.1109/ICDE51399.2021.00276(2435-2446)Online publication date: Apr-2021
https://doi.org/10.1109/ICDE51399.2021.00276

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An Architecture of an Academic Search Engine with Personalized Search Result Ranking Mechanism

A method for personalized ranking of items based on similarity between Twitter users