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IQ: The Case for Iterative Querying for Knowledge

Summary: Argues for Iterative Querying (IQ): interactive query refinement and relaxation for knowledge-centric search over schema-less graph data, moving beyond single-shot SPARQL/keyword queries. Presents two instantiations—keyword+structural constraints and SPARQL extensions—and highlights open research challenges. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
174
Venue
CIDR
Year
2011
Pagerank
5.2521703e-05
Overall Rank
9,588 | 34.22%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{mass_cidr11,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '11},
        title = {{IQ: The Case for Iterative Querying for Knowledge}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Mass, Yosi and Ramanath, Maya and Sagiv, Yehoshua and Weikum, Gerhard},
        year = {2011}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
5,971 Lenses: An On-Demand Approach to ETL 2015 VLDB 6.0243066e-05
9,652 Finding a Minimal Tree Pattern Under Neighborhood Constraints 2011 PODS 5.2426111e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,542 Keyword Proximity Search in Complex Data Graphs 2008 SIGMOD 0.00010421046
2,832 Expressive and Flexible Access to Web-Extracted Data: A Keyword-based Structured Query Language 2010 SIGMOD 8.0783003e-05
4,461 Extracting and Querying a Comprehensive Web Database 2009 CIDR 6.6889881e-05
12,434 Exploratory Keyword Search on Data Graphs 2010 SIGMOD 5.093636e-05
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