Cited by 79Information Retrieval and Search BehaviorRecommender Systems and TechniquesTopic Modeling

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Amazon Search: The Joy of Ranking Products

Sorokina, Daria, Cantu-Paz, Erick·2016·Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval

DOI 10.1145/2911451.2926725

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Abstract

Amazon is one of the world's largest e-commerce sites and Amazon Search powers the majority of Amazon's sales. As a consequence, even small improvements in relevance ranking both positively influence the shopping experience of millions of customers and significantly impact revenue. In the past, Amazon's product search engine consisted of several hand-tuned ranking functions using a handful of input features. A lot has changed since then. In this talk we are going to cover a number of relevance algorithms used in Amazon Search today. We will describe a general machine learning framework used for ranking within categories, blending separate rankings in All Product Search, NLP techniques used for matching queries and products, and algorithms targeted at unique tasks of specific categories --- books and fashion.

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Preface
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Searching Personal Collections
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Authors’ Biography/Index
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Introduction
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Authors: Sorokina, D., & Cantu-Paz, E.
Affiliations: A9.com, Palo Alto, CA, USA
Venue: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval
Publisher: ACM
Published: 2016-07-07
Pages: 459-460
DOI: 10.1145/2911451.2926725
OpenAlex: W2463133191
Semantic Scholar: a5c944bff425cbe4bb332be40f0ef55ba2bbb06c
Cited by: 71
References: 3
Citations by year: 2026: 2 · 2025: 3 · 2024: 26 · 2023: 9 · 2022: 10 · 2021: 8 · 2020: 5 · 2019: 7 · 2018: 1
FWCI: 2.26
Type: conference paper
Language: en
Open access: closed
Licence: www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations: International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) (publishedVersion)
Topics: Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
Keywords: search engine ranking, relevance ranking, e-commerce search engines, product search

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Amazon Search: The Joy of Ranking Products

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