SHOAL: Large-scale Hierarchical Taxonomy via Graph-based Query Coalition in E-commerce

Summary: SHOAL builds a scalable hierarchical taxonomy via graph-based query coalition, mapping items to query-labeled topics that reflect user intent. Enables explainable alignment with ontology, achieving 98% precision and 5% CTR lift; deployed at Alibaba. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 11885
Venue: VLDB
Year: 2019
Pagerank: 4.613363e-05
Overall Rank: 7,945 | 44.73%
DOI: 10.14778/3352063.3352084

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
11,621	HDAG-Explorer: A System for Hierarchical DAG Summarization and Exploration	2020	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

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

Rank	Cited Paper	Year	Venue	Pagerank

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