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Efficient and Effective KNN Sequence Search with Approximate n-grams

Summary: Proposes KNN sequence search under edit distance using longer approximate n-grams for pruning with a two-level index. CA-based filtering with a frequency queue reduces false positives, enabling progressive results and early termination; parallel execution scales. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10949
Venue
VLDB
Year
2014
Pagerank
5.1559617e-05
Overall Rank
10,086 | 30.81%
DOI
10.14778/2732232.2732236

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{wang_vldb14,
        title = {{Efficient and Effective KNN Sequence Search with Approximate n-grams}},
        author = {Wang, Xiaoli and Ding, Xiaofeng and Tung, Anthony K.H. and Zhang, Zhenjie},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {1},
        pages = {1--12},
        doi = {10.14778/2732232.2732236},
        url = {https://doi.org/10.14778/2732232.2732236},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
5,726 Pigeonring: A Principle for Faster Thresholded Similarity Search 2019 VLDB 6.1079184e-05
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