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Interactive Graph Search Made Simple

Summary: An algorithmic framework for Interactive Graph Search that reduces design to two black-box operations. Simple black-box instantiations yield optimal interaction rounds and substantially lower CPU time, with extensive real/synthetic validation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7297
Venue
SIGMOD
Year
2025
Pagerank
4.1945683e-05
Overall Rank
10,519 | 26.83%
DOI
10.1145/3725409

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,091 LLM-Powered Interactive Graph Search: A Scalable and Practical Approach 2026 SIGMOD 4.1945683e-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.

Rank Cited Paper Year Venue Pagerank
697 Human-Assisted Graph Search: It’s Okay to Ask Questions 2011 VLDB 0.00018043655
5,734 Efficient Algorithms for Crowd-Aided Categorization 2020 VLDB 5.3482904e-05
6,584 Budget Constrained Interactive Search for Multiple Targets 2021 VLDB 5.0027686e-05
7,535 Interactive Graph Search 2019 SIGMOD 4.7178467e-05
9,372 Optimal Algorithms for Multiway Search on Partial Orders 2022 PODS 4.3480577e-05
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