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)

Paper ID: h122c7b14496d834c
Venue: SIGMOD
Year: 2014
Pagerank: 5.5779439e-05
Overall Rank: 7,230 | 51.41%
DOI: 10.1145/2588555.2610514

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
6,091	Lenses: An On-Demand Approach to ETL	2015	VLDB	5.8880755e-05
7,505	Crowdsourced Data Management: Overview and Challenges	2017	SIGMOD	5.5057737e-05
7,954	A Natural Language Interface for Querying General and Individual Knowledge	2015	VLDB	5.4182701e-05
8,959	Managing General and Individual Knowledge in Crowd Mining Applications	2015	CIDR	5.2496174e-05
9,459	Ontology Assisted Crowd Mining	2014	VLDB	5.1727984e-05
12,234	ZigZag: Supporting Similarity Queries on Vector Space Models	2018	SIGMOD	4.9769913e-05
12,320	DOCS: Domain-Aware Crowdsourcing System	2017	VLDB	4.9769913e-05
12,364	December: A Declarative Tool for Crowd Member Selection	2016	VLDB	4.9769913e-05
12,410	NL2CM: A Natural Language Interface to Crowd Mining	2015	SIGMOD	4.9769913e-05

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	0.00025546182
476	Mining Generalized Association Rules	1995	VLDB	0.00017664233
750	So Who Won? Dynamic Max Discovery with the Crowd	2012	SIGMOD	0.00014258988
871	Leveraging Transitive Relations for Crowdsourced Joins	2013	SIGMOD	0.00013338722
987	CrowdScreen: Algorithms for Filtering Data with Humans	2012	SIGMOD	0.00012655094
1,265	CDAS: A Crowdsourcing Data Analytics System	2012	VLDB	0.00011277921
1,926	Counting with the Crowd	2013	VLDB	9.3636304e-05
2,832	Crowd Mining	2013	SIGMOD	7.9554419e-05
7,091	Answering Planning Queries with the Crowd	2013	VLDB	5.5991673e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	1,265	CDAS: A Crowdsourcing Data Analytics System	2012	VLDB
2	7,789	Pushing the Boundaries of Crowd-enabled Databases with Query-driven Schema Expansion	2012	VLDB
3	92	CrowdDB: Answering Queries with Crowdsourcing	2011	SIGMOD
4	12,480	Online Ordering of Overlapping Data Sources	2014	VLDB
5	8,960	CrowdMiner: Mining association rules from the crowd	2013	VLDB
6	5,615	CrowdQ: Crowdsourced Query Understanding	2013	CIDR
7	12,410	NL2CM: A Natural Language Interface to Crowd Mining	2015	SIGMOD
8	2,832	Crowd Mining	2013	SIGMOD
9	8,959	Managing General and Individual Knowledge in Crowd Mining Applications	2015	CIDR
10	9,459	Ontology Assisted Crowd Mining	2014	VLDB