QC-Trees: An Efficient Summary Structure for Semantic OLAP
Summary: QC-Trees proposes a compact, direct representation for semantic OLAP summaries, replacing the quotient cube with the QC-tree. It provides algorithms for construction, query answering, and incremental maintenance, and demonstrates space/time gains over prior approaches. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Laks V.S. Lakshmanan (University of British Columbia)
- 2. Jian Pei (State University of New York at Buffalo)
- 3. Yan Zhao (University of British Columbia)
BibTeX Citation
@inproceedings{lakshmanan_sigmod03,
title = {{QC-Trees: An Efficient Summary Structure for Semantic OLAP}},
author = {Lakshmanan, Laks V.S. and Pei, Jian and Zhao, Yan},
series = {{SIGMOD} '03},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/872757.872768},
url = {https://dl.acm.org/doi/10.1145/872757.872768},
year = {2003}
}
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