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Pushing the Boundaries of Crowd-enabled Databases with Query-driven Schema Expansion

Summary: Extends crowd-enabled databases with query-driven schema expansion for on-demand attributes. It leverages perceptual spaces learned from social web ratings and few expert samples to automatically infer missing data, reducing crowdsourcing cost while maintaining high quality. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10499
Venue
VLDB
Year
2012
Pagerank
4.7075553e-05
Overall Rank
7,572 | 47.33%
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
4,827 An Online Cost Sensitive Decision-Making Method in Crowdsourcing Systems 2013 SIGMOD 5.8938399e-05
7,113 Answering Planning Queries with the Crowd 2013 VLDB 4.8274062e-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
94 CrowdDB: Answering Queries with Crowdsourcing 2011 SIGMOD 0.00051013264
119 Answering Queries using Humans, Algorithms and Databases 2011 CIDR 0.0004564788
249 Crowdsourced Databases: Query Processing with People 2011 CIDR 0.00030740523
2,333 A Platform for Personal Information Management and Integration 2005 CIDR 9.0169986e-05
6,713 Query Relaxation Using Malleable Schemas 2007 SIGMOD 4.951387e-05
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