Diversity based Relevance Feedback for Time Series Search

Summary: Diversity-based relevance feedback for time series search using dual-tree CWT and SAX representations to boost retrieval accuracy. Representation-aware feedback with weighting for single and multi-representation cases yields gains with simple NN and claims diversification via representation feedback. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 10957
Venue: VLDB
Year: 2014
Pagerank: 5.4155551e-05
Overall Rank: 8,485 | 41.79%
DOI: 10.14778/2732228.2732230

Incoming Non-self Citations Over Time

Authors

1. Bahaeddin Eravci (Bilkent University)
2. Hakan Ferhatosmanoglu (Bilkent University)

BibTeX Citation

@article{eravci_vldb14,
        title = {{Diversity based Relevance Feedback for Time Series Search}},
        author = {Eravci, Bahaeddin and Ferhatosmanoglu, Hakan},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {2},
        doi = {10.14778/2732228.2732230},
        url = {https://doi.org/10.14778/2732228.2732230},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
6,200	New Trends on Exploratory Methods for Data Analytics	2017	VLDB	5.9457282e-05
8,358	Exploring the Data Wilderness through Examples	2019	SIGMOD	5.4446041e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
1,862	MindReader: Querying databases through multiple examples	1998	VLDB	9.5951515e-05
3,881	Using Trees to Depict a Forest	2009	VLDB	7.0490549e-05
6,483	Similarity Search: A Matching Based Approach	2006	VLDB	5.8667204e-05

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