Searching Large Lexicons for Partially Specified Terms using Compressed Inverted Files

Summary: In-memory lexicon search via compressed inverted files enables fast matching of partially specified terms. Memory-efficient inverted indices for main-memory databases deliver orders-of-magnitude speedups with less memory than pointer-heavy alternatives. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h73880963e3d96c50
Venue: VLDB
Year: 1993
Pagerank: 6.8907318e-05
Overall Rank: 3,966 | 73.34%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. Justin Zobel (Collaborative Information Technology Research Institute; Royal Melbourne Institute of Technology)
2. Alistair Moffat (University of Melbourne)
3. Ron Sacks-Davis (Collaborative Information Technology Research Institute)

BibTeX Citation

@article{zobel_vldb93,
        title = {{Searching Large Lexicons for Partially Specified Terms using Compressed Inverted Files}},
        author = {Zobel, Justin and Moffat, Alistair and Sacks-Davis, Ron},
        journal = {PVLDB},
        series = {{VLDB} '93},
        pages = {290--301},
        year = {1993}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
303	Proximity Search in Databases	1998	VLDB	0.0002164278
1,618	Efficient Processing of Joins on Set-valued Attributes	2003	SIGMOD	0.00010056773

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
1,624	An Efficient Indexing Technique for Full-Text Database Systems	1992	VLDB	0.00010045219

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