December: A Declarative Tool for Crowd Member Selection
Summary: December is a declarative tool for crowd member selection using Member-QL to express profile, history, similarity, and task relevance. It provides semantically aware similarity and expertise in novel, efficient algorithms for holistic crowdsourcing. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yael Amsterdamer
- 2. Tova Milo
- 3. Amit Somech
- 4. Brit Youngmann
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,322 | iCrowd: An Adaptive Crowdsourcing Framework | 2015 | SIGMOD | 7.2230626e-05 |
| 5,588 | Worker Skill Estimation in Team-Based Tasks | 2015 | VLDB | 5.4218199e-05 |
| 7,224 | OASSIS: Query Driven Crowd Mining | 2014 | SIGMOD | 4.7959024e-05 |
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| 11,788 | CDB: Optimizing Queries with Crowd-Based Selections and Joins | 2017 | SIGMOD | 4.1945683e-05 |