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SOCQET: Semantic OLAP with Compressed Cube and Summarization

Summary: SOCQET introduces quotient cubes: group cube cells by semantics (base tuples rolled up), yielding a smaller quotient lattice for semantic OLAP. It materializes quotient cubes to answer queries, enables class-based navigation and drill-down, and shows gains with a prototype engine and semantic compression. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3475
Venue
SIGMOD
Year
2003
Pagerank
5.3244898e-05
Overall Rank
5,795 | 59.69%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
3,536 General purpose database summarization 2005 VLDB 6.9990821e-05
7,141 Efficient Error-tolerant Query Autocompletion 2013 VLDB 4.8197901e-05
11,026 Improving Graph Compression for Efficient Resource-Constrained Graph Analytics 2024 VLDB 4.1945683e-05
11,224 Homomorphic Compression: Making Text Processing on Compression Unlimited 2023 SIGMOD 4.1945683e-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
3,590 Quotient Cube: How to Summarize the Semantics of a Data Cube 2002 VLDB 6.9421381e-05
4,005 QC-Trees: An Efficient Summary Structure for Semantic OLAP 2003 SIGMOD 6.5414308e-05
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