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 (Tel Aviv University)
- 2. Susan B. Davidson (University of Pennsylvania)
- 3. Tova Milo (Tel Aviv University)
- 4. Slava Novgorodov (Tel Aviv University)
- 5. Amit Somech (Tel Aviv University)
BibTeX Citation
@inproceedings{amsterdamer_sigmod14,
title = {{OASSIS: Query Driven Crowd Mining}},
author = {Amsterdamer, Yael and Davidson, Susan B. and Milo, Tova and Novgorodov, Slava and Somech, Amit},
series = {{SIGMOD} '14},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2588555.2610514},
url = {https://dl.acm.org/doi/10.1145/2588555.2610514},
year = {2014}
}Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,089 | Lenses: An On-Demand Approach to ETL | 2015 | VLDB | 5.8908642e-05 |
| 7,500 | Crowdsourced Data Management: Overview and Challenges | 2017 | SIGMOD | 5.5083793e-05 |
| 7,950 | A Natural Language Interface for Querying General and Individual Knowledge | 2015 | VLDB | 5.4207861e-05 |
| 8,951 | Managing General and Individual Knowledge in Crowd Mining Applications | 2015 | CIDR | 5.252096e-05 |
| 9,450 | Ontology Assisted Crowd Mining | 2014 | VLDB | 5.1752483e-05 |
| 12,228 | ZigZag: Supporting Similarity Queries on Vector Space Models | 2018 | SIGMOD | 4.9793485e-05 |
| 12,314 | DOCS: Domain-Aware Crowdsourcing System | 2017 | VLDB | 4.9793485e-05 |
| 12,358 | December: A Declarative Tool for Crowd Member Selection | 2016 | VLDB | 4.9793485e-05 |
| 12,404 | NL2CM: A Natural Language Interface to Crowd Mining | 2015 | SIGMOD | 4.9793485e-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 |
|---|---|---|---|---|
| 198 | CrowdER: Crowdsourcing Entity Resolution | 2012 | VLDB | 0.00025555196 |
| 475 | Mining Generalized Association Rules | 1995 | VLDB | 0.00017672519 |
| 749 | So Who Won? Dynamic Max Discovery with the Crowd | 2012 | SIGMOD | 0.00014265279 |
| 871 | Leveraging Transitive Relations for Crowdsourced Joins | 2013 | SIGMOD | 0.00013343705 |
| 987 | CrowdScreen: Algorithms for Filtering Data with Humans | 2012 | SIGMOD | 0.00012660627 |
| 1,264 | CDAS: A Crowdsourcing Data Analytics System | 2012 | VLDB | 0.0001128316 |
| 1,926 | Counting with the Crowd | 2013 | VLDB | 9.3637786e-05 |
| 2,832 | Crowd Mining | 2013 | SIGMOD | 7.9590386e-05 |
| 7,089 | Answering Planning Queries with the Crowd | 2013 | VLDB | 5.6018191e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 1,264 | CDAS: A Crowdsourcing Data Analytics System | 2012 | VLDB |
| 2 | 7,782 | Pushing the Boundaries of Crowd-enabled Databases with Query-driven Schema Expansion | 2012 | VLDB |
| 3 | 92 | CrowdDB: Answering Queries with Crowdsourcing | 2011 | SIGMOD |
| 4 | 12,474 | Online Ordering of Overlapping Data Sources | 2014 | VLDB |
| 5 | 8,952 | CrowdMiner: Mining association rules from the crowd | 2013 | VLDB |
| 6 | 5,614 | CrowdQ: Crowdsourced Query Understanding | 2013 | CIDR |
| 7 | 12,404 | NL2CM: A Natural Language Interface to Crowd Mining | 2015 | SIGMOD |
| 8 | 2,832 | Crowd Mining | 2013 | SIGMOD |
| 9 | 8,951 | Managing General and Individual Knowledge in Crowd Mining Applications | 2015 | CIDR |
| 10 | 9,450 | Ontology Assisted Crowd Mining | 2014 | VLDB |