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Indexing for Interactive Exploration of Big Data Series
Summary: Adaptive indexing for big data series builds index parts on demand for regions touched by queries. Enables immediate exploration and large latency reductions, answering ~3×10^5 queries before conventional up-front indexing finishes indexing 1B series.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
h3542d8b3f0aa3560
Venue
SIGMOD
Year
2014
Pagerank
6.30259e-05
Overall Rank
5,013 | 66.40%
DOI
10.1145/2588555.2610498
Incoming Non-self Citations Over Time
BibTeX Citation
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@inproceedings{zoumpatianos_sigmod14,
title = {{Indexing for Interactive Exploration of Big Data Series}},
author = {Zoumpatianos, Kostas and Idreos, Stratos and Palpanas, Themis},
series = {{SIGMOD} '14},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2588555.2610498},
url = {https://dl.acm.org/doi/10.1145/2588555.2610498},
year = {2014}
}
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Pagerank
2
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1994
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1996
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253
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CIDR
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2004
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