OASSIS: Query Driven Crowd Mining
Summary: OASSIS enables query-driven crowd mining for frequent, significant patterns via general questions to crowd data. It merges ontological knowledge with user history, offers a declarative query language and efficient evaluator, and returns concise answers while minimizing crowd questions through an interactive UI, validated on real and synthetic data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yael Amsterdamer
- 2. Susan B. Davidson
- 3. Tova Milo
- 4. Slava Novgorodov
- 5. Amit Somech
Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,779 | Lenses: An On-Demand Approach to ETL | 2015 | VLDB | 5.3307398e-05 |
| 7,117 | Crowdsourced Data Management: Overview and Challenges | 2017 | SIGMOD | 4.826509e-05 |
| 7,780 | A Natural Language Interface for Querying General and Individual Knowledge | 2015 | VLDB | 4.6533677e-05 |
| 8,694 | Managing General and Individual Knowledge in Crowd Mining Applications | 2015 | CIDR | 4.4661379e-05 |
| 9,212 | Ontology Assisted Crowd Mining | 2014 | VLDB | 4.3722536e-05 |
| 11,724 | ZigZag: Supporting Similarity Queries on Vector Space Models | 2018 | SIGMOD | 4.1945683e-05 |
| 11,816 | DOCS: Domain-Aware Crowdsourcing System | 2017 | VLDB | 4.1945683e-05 |
| 11,864 | December: A Declarative Tool for Crowd Member Selection | 2016 | VLDB | 4.1945683e-05 |
| 11,912 | NL2CM: A Natural Language Interface to Crowd Mining | 2015 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 263 | CrowdER: Crowdsourcing Entity Resolution | 2012 | VLDB | 0.00029862413 |
| 403 | Mining Generalized Association Rules | 1995 | VLDB | 0.00024148455 |
| 859 | So Who Won? Dynamic Max Discovery with the Crowd | 2012 | SIGMOD | 0.00015870894 |
| 866 | Leveraging Transitive Relations for Crowdsourced Joins | 2013 | SIGMOD | 0.00015801196 |
| 1,164 | CrowdScreen: Algorithms for Filtering Data with Humans | 2012 | SIGMOD | 0.00013564823 |
| 1,491 | CDAS: A Crowdsourcing Data Analytics System | 2012 | VLDB | 0.00011694982 |
| 2,334 | Counting with the Crowd | 2013 | VLDB | 9.0161817e-05 |
| 3,100 | Crowd Mining | 2013 | SIGMOD | 7.5634778e-05 |
| 7,113 | Answering Planning Queries with the Crowd | 2013 | VLDB | 4.8274062e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,491 | CDAS: A Crowdsourcing Data Analytics System | 2012 | VLDB | 0.00011694982 |
| 7,572 | Pushing the Boundaries of Crowd-enabled Databases with Query-driven Schema Expansion | 2012 | VLDB | 4.7075553e-05 |
| 94 | CrowdDB: Answering Queries with Crowdsourcing | 2011 | SIGMOD | 0.00051013264 |
| 11,985 | Online Ordering of Overlapping Data Sources | 2014 | VLDB | 4.1945683e-05 |
| 8,695 | CrowdMiner: Mining association rules from the crowd | 2013 | VLDB | 4.4661379e-05 |
| 3,935 | CrowdQ: Crowdsourced Query Understanding | 2013 | CIDR | 6.6163464e-05 |
| 11,912 | NL2CM: A Natural Language Interface to Crowd Mining | 2015 | SIGMOD | 4.1945683e-05 |
| 3,100 | Crowd Mining | 2013 | SIGMOD | 7.5634778e-05 |
| 8,694 | Managing General and Individual Knowledge in Crowd Mining Applications | 2015 | CIDR | 4.4661379e-05 |
| 9,212 | Ontology Assisted Crowd Mining | 2014 | VLDB | 4.3722536e-05 |