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Automatic Categorization of Query Results

Summary: Dynamic, labeled hierarchical categorization of SQL query results to curb information overload. Models user overload, treats categorization as a min-cost optimization, and uses heuristics to generate relevant categories for targeted exploration. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3565
Venue
SIGMOD
Year
2004
Pagerank
9.5498009e-05
Overall Rank
2,096 | 85.43%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 10 of 10 citing papers.

Rank Citing Paper Year Venue Pagerank
1,258 Ordering the Attributes of Query Results 2006 SIGMOD 0.00013013676
1,605 Addressing Diverse User Preferences in SQL-Query-Result Navigation 2007 SIGMOD 0.00011186762
5,419 Combining Keyword Search and Forms for Ad Hoc Querying of Databases 2009 SIGMOD 5.5176475e-05
6,584 Budget Constrained Interactive Search for Multiple Targets 2021 VLDB 5.0027686e-05
6,653 Supporting Ranking and Clustering as Generalized Order-By and Group-By 2007 SIGMOD 4.9735307e-05
6,959 Supporting OLAP Operations over Imperfectly Integrated Taxonomies 2008 SIGMOD 4.8857059e-05
8,206 Query Expansion Based on Clustered Results 2011 VLDB 4.5586037e-05
9,573 DataLens: Making a Good First Impression 2009 SIGMOD 4.3254101e-05
12,315 Exploring Biomedical Databases with BioNav 2009 SIGMOD 4.1945683e-05
12,563 Database-Inspired Search 2005 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

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