Summary: Revisits PLA for time-series similarity search, with a PLA-space distance that lower-bounds Euclidean distance for exact pruning. Proposes an indexable PLA framework using these bounds, achieving strong pruning and faster search than APCA and CP.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
9788
Venue
VLDB
Year
2007
Pagerank
9.9227051e-05
Overall Rank
1,722 | 88.19%
DOI
-
Incoming Non-self Citations Over Time
Authors
1.
Qiuxia Chen
(Hong Kong University of Science and Technology)
2.
Lei Chen
(Hong Kong University of Science and Technology)
3.
Xiang Lian
(Hong Kong University of Science and Technology)
4.
Yunhao Liu
(Hong Kong University of Science and Technology)
@article{chen_vldb07,
title = {{Indexable PLA for Efficient Similarity Search}},
author = {Chen, Qiuxia and Chen, Lei and Lian, Xiang and Liu, Yunhao and Yu, Jeffrey Xu},
journal = {PVLDB},
series = {{VLDB} '07},
pages = {435},
year = {2007}
}