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Efficiently Answering Top-k Typicality Queries on Large Databases

Summary: Applies psychological typicality to databases, defining top-k simple and discriminative typicality for representative or distinguishing instances. Presents approximations: linear-time tournament; VP-tree local typicality with guarantees; Local Typicality Tree index; experiments show practicality. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9639
Venue
VLDB
Year
2007
Pagerank
6.1327917e-05
Overall Rank
4,504 | 68.67%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank Citing Paper Year Venue Pagerank
3,654 Using Trees to Depict a Forest 2009 VLDB 6.873144e-05
3,928 Tighter Estimation using Bottom-k Sketches 2008 VLDB 6.6254568e-05
4,080 Sliding-Window Top-k Queries on Uncertain Streams 2008 VLDB 6.4652983e-05
5,373 Robust and Efficient Algorithms for Rank Join Evaluation 2009 SIGMOD 5.5425231e-05
6,080 Answering Top-k Representative Queries on Graph Databases 2014 SIGMOD 5.2214553e-05
8,507 ARCube: Supporting Ranking Aggregate Queries in Partially Materialized Data Cubes 2008 SIGMOD 4.4955397e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

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