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COSMO: A Large-Scale E-commerce Common Sense Knowledge Generation and Serving System at Amazon

Summary: COSMO: scalable pipeline to mine user-centric commonsense from behaviors, with LLM seeds refined by critic classifiers. COSMO-LM is instruction-tuned to expand KG to 18, delivering millions of facts from 30k annotations, deployed in Amazon search. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6806
Venue
SIGMOD
Year
2024
Pagerank
4.4279221e-05
Overall Rank
8,887 | 38.18%
DOI
10.1145/3626246.3653398

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
5,233 RoarGraph: A Projected Bipartite Graph for Efficient Cross-Modal Approximate Nearest Neighbor Search 2024 VLDB 5.6131833e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
2,163 Elastic Machine Learning Algorithms in Amazon SageMaker 2020 SIGMOD 9.3949234e-05
4,114 AliCoCo: Alibaba E-commerce Cognitive Concept Net 2020 SIGMOD 6.439922e-05
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