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CrowdMatcher: Crowd-Assisted Schema Matching

Summary: Hybrid machine-crowd schema matching integrates multiple matchers to address uncertainty in schema semantics. CCQs crowd-verify correspondences, select informative queries to minimize cost, tolerate noise, and update results with crowd feedback. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4823
Venue
SIGMOD
Year
2014
Pagerank
6.1975384e-05
Overall Rank
4,414 | 69.33%
DOI
10.1145/2588555.2594515

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
2,805 Query-Oriented Data Cleaning with Oracles 2015 SIGMOD 8.103731e-05
7,780 A Natural Language Interface for Querying General and Individual Knowledge 2015 VLDB 4.6489024e-05
9,218 QOCO: A Query Oriented Data Cleaning System with Oracles 2015 VLDB 4.3672293e-05
11,920 NL2CM: A Natural Language Interface to Crowd Mining 2015 SIGMOD 4.1905499e-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
174 Schema Mapping as Query Discovery 2000 VLDB 0.00038586435
718 Data Integration with Uncertainty 2007 VLDB 0.00017558942
1,862 Bootstrapping Pay-As-You-Go Data Integration Systems 2008 SIGMOD 0.00010292134
5,080 Reducing Uncertainty of Schema Matching via Crowdsourcing 2013 VLDB 5.7081186e-05
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