Understanding local structure in ranked datasets

Summary: Defines “local structure” in ranked datasets—agreement of ranker subsets over item subsets—enabling localized consensus/conflict analysis yet hard to model and compute. Advocates combining declarative, incremental DB primitives with ML/data‑mining and outlines a roadmap for a scalable framework. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 203
Venue: CIDR
Year: 2013
Pagerank: 4.8603531e-05
Overall Rank: 7,008 | 51.30%
DOI: -

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
4,804	A System for Management and Analysis of Preference Data	2014	VLDB	5.906327e-05
5,689	Rank aggregation with ties: Experiments and Analysis	2015	VLDB	5.3706419e-05

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank

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