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Query Expansion Based on Clustered Results

Summary: Cluster results at user granularity to yield one expanded query per cluster. Formalizes APX-hardness and offers two algorithms—iterative single-keyword refinement and partial elimination based convergence—that produce a cluster-aware expansion set. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10264
Venue
VLDB
Year
2011
Pagerank
4.5586037e-05
Overall Rank
8,206 | 42.92%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
5,644 FluxQuery: An Execution Framework for Highly Interactive Query Workloads 2016 SIGMOD 5.3924275e-05
6,210 Summarizing Answer Graphs Induced by Keyword Queries 2013 VLDB 5.1560547e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,667 Structured Search Result Differentiation 2009 VLDB 0.00010960247
2,096 Automatic Categorization of Query Results 2004 SIGMOD 9.5498009e-05
2,813 Mining Search Engine Query Logs via Suggestion Sampling 2008 VLDB 8.0773142e-05
3,654 Using Trees to Depict a Forest 2009 VLDB 6.873144e-05
4,474 Measure-driven Keyword-Query Expansion 2009 VLDB 6.1528736e-05
5,541 Query Biased Snippet Generation in XML Search 2008 SIGMOD 5.4492586e-05
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