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META: An Efficient Matching-Based Method for Error-Tolerant Autocompletion

Summary: Meta proposes a matching-based framework for error-tolerant autocompletion, replacing trie-centric active-node computation with character-level matching. It introduces a compact tree index to maintain active nodes, an incremental top-k algorithm, and achieves 1–2 orders of magnitude speedups over state-of-the-art on real datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11558
Venue
VLDB
Year
2016
Pagerank
5.2351259e-05
Overall Rank
9,705 | 33.42%
DOI
10.14778/2977797.2977808

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{deng_vldb16,
        title = {{META: An Efficient Matching-Based Method for Error-Tolerant Autocompletion}},
        author = {Deng, Dong and Li, Guoliang and Wen, He and Jagadish, H. V. and Feng, Jianhua},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {10},
        pages = {828--839},
        doi = {10.14778/2977797.2977808},
        url = {https://doi.org/10.14778/2977797.2977808},
        year = {2016}
}

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