Odyssey: A Journey in the Land of Distributed Data Series Similarity Search
Summary: Odyssey is a distributed data-series similarity-search framework exploiting multicore clusters for scalable indexing and query processing. Its key innovations are data-movement-avoiding scheduling/load balancing and flexible partial replication, trading data scalability against query performance. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Manos Chatzakis (EPFL)
- 2. Panagiota Fatourou (Foundation for Research and Technology-Hellas; University of Crete)
- 3. Eleftherios Kosmas (Foundation for Research and Technology-Hellas; Hellenic Mediterranean University; University of Crete)
- 4. Themis Palpanas (Institut Universitaire de France; Université Paris Cité)
- 5. Botao Peng (Chinese Academy of Sciences; Institute of Computing Technology)
BibTeX Citation
@article{chatzakis_vldb23,
title = {{Odyssey: A Journey in the Land of Distributed Data Series Similarity Search}},
author = {Chatzakis, Manos and Fatourou, Panagiota and Kosmas, Eleftherios and Palpanas, Themis and Peng, Botao},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {5},
pages = {1140--1153},
doi = {10.14778/3579075.3579087},
url = {https://doi.org/10.14778/3579075.3579087},
year = {2023}
}
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