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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
10265
Venue
VLDB
Year
2011
Pagerank
4.5542351e-05
Overall Rank
8,206 | 42.97%
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
5,657 FluxQuery: An Execution Framework for Highly Interactive Query Workloads 2016 SIGMOD 5.3873634e-05
6,208 Summarizing Answer Graphs Induced by Keyword Queries 2013 VLDB 5.1511024e-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
1,664 Structured Search Result Differentiation 2009 VLDB 0.0001096091
2,101 Automatic Categorization of Query Results 2004 SIGMOD 9.5406958e-05
2,817 Mining Search Engine Query Logs via Suggestion Sampling 2008 VLDB 8.0695314e-05
3,651 Using Trees to Depict a Forest 2009 VLDB 6.8727613e-05
4,475 Measure-driven Keyword-Query Expansion 2009 VLDB 6.1469582e-05
5,549 Query Biased Snippet Generation in XML Search 2008 SIGMOD 5.4440282e-05
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