DBScholar

Back to papers

Odyssey: An Engine Enabling The Time-Series Clustering Journey

Summary: Odyssey is a modular web engine that rigorously benchmarks 80 time‑series clustering methods across 9 classes on 128 diverse datasets. It exposes overlooked high-performing classes, challenges elastic-distance and deep‑learning claims, and finds no method significantly outperforming k‑Shape. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13455
Venue
VLDB
Year
2023
Pagerank
5.2634238e-05
Overall Rank
9,477 | 34.98%
DOI
10.14778/3611540.3611622

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{paparrizos_vldb23,
        title = {{Odyssey: An Engine Enabling The Time-Series Clustering Journey}},
        author = {Paparrizos, John and Reddy, Sai Prasanna Teja},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {12},
        pages = {4066--4069},
        doi = {10.14778/3611540.3611622},
        url = {https://doi.org/10.14778/3611540.3611622},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 11 of 11 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers